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Trends in the CO andC2H6 partial columns ~0–15 km) have been estimated from four European ground-based solar FTIR (Fourier Transform InfraRed) stations for the 1996–2006 time period. The CO trends from the four stations Jungfraujoch, Zugspitze, Harestua and Kiruna have been estimated to −0.45 ± 0.16% yr−1, −1.00 ± 0.24% yr−1, −0.62 ± 0.19 % yr−1 and −0.61 ± 0.16% yr−1, respectively. The corresponding trends for C2H6 are −1.51 ± 0.23% yr−1, −2.11 ± 0.30% yr−1, −1.09 ± 0.25% yr−1 and −1.14 ± 0.18% yr−1. All trends are presented with their 2-σ confidence intervals. To find possible reasons for the CO trends, the global-scale EMEP MSC-W chemical transport model has been used in a series of sensitivity scenarios. It is shown that the trends are consistent with the combination of a 20% decrease in the anthropogenic CO emissions seen in Europe and North America during the 1996–2006 period and a 20% increase in the anthropogenic CO emissions in East Asia, during the same time period. The possible impacts of CH4 and biogenic volatile organic compounds (BVOCs) are also considered. The European and global-scale EMEP models have been evaluated against the measured CO and C2H6 partial columns from Jungfraujoch, Zugspitze, Bremen, Harestua, Kiruna and Ny-Ålesund. The European model reproduces, on average the measurements at the different sites fairly well and within 10–22% deviation for CO and 14–31% deviation for C2H6. Their seasonal amplitude is captured within 6–35% and 9–124% for CO and C2H6, respectively. However, 61–98% of the CO and C2H6 partial columns in the European model are shown to arise from the boundary conditions, making the global-scale model a more suitable alternative when modeling these two species. In the evaluation of the global model the average partial columns for 2006 are shown to be within 1–9% and 37–50% of the measurements for CO and C2H6, respectively. The global model sensitivity for assumptions made in this paper is also analyzed.

We present a full-mission data product of carbon monoxide (CO) vertical column densities using the 2310–2338 nm SCIAMACHY reflectance measurements over clear sky land scenes for the period January 2003–April 2012. The retrieval employs the SICOR algorithm, which will be used for operational data processing of the Sentinel-5 Precursor mission, combined with a SCIAMACHY specific radiometric soft-calibration to mitigate instrumental issues. The retrieval approach infers simultaneously carbon monoxide, methane and water vapour column densities together with a Lambertian surface albedo from individual SCIAMACHY measurements employing a non-scattering radiative transfer model. To account for the radiometric instrument degradation including the formation of an ice-layer on the 2.3 μm detector-array, we consider clear sky measurements over the Sahara as a natural calibration target. For these specific measurements, we spectrally calibrate the SCIAMACHY measurements and determine a spectral radiometric offset and the width of the instrument spectral response function as a function of time for the entire operational phase of the mission. We show that the smoothing error of individual clear sky CO retrievals is less than ±1 ppb and thus this error contribution has not to be accounted for in the validation considering the much higher retrieval noise. The CO data product is validated against measurements of ground-based Fourier transform infrared spectrometers at 27 stations of the NDACC-IRWG and TCCON network and MOZAIC/IAGOS aircraft measurements at 26 airports worldwide. Overall, we find a good agreement with TCCON measurements with a mean bias b = −1.2 ppb and a station-to-station bias with σ = 7.2 ppb. For the NDACC-IRWG network, we obtain a larger mean station bias of b = −9.2 ppb with σ = 8.1 ppb and for the MOZAIC/IAGOS measurements we find b = −6.4 ppb with σ = 5.6 ppb. The SCIAMACHY data set is subject to a small but significant trend of 1.47 ± 0.25 ppb yr−1. After trend correction, the bias with respect to MOZAIC/IAGOS observation is 2.5 ppb, with respect to TCCON measurements it is −4.6 ppb and with respect to NDACC-IRWG measurements −8.4 ppb. Hence, a discrepancy of 3.8 ppb remains between the global biases with NDACC-IRWG and TCCON, which is confirmed by directly comparing NDACC-IRWG and TCCON measurements. Generally, the scatter of the individual SCIAMACHY CO retrievals is high and dominated by large measurement noise. Hence, for practical usage of the dataset, averaging of individual retrievals is required. As an example, we show that monthly mean SCIAMACHY CO retrievals, averaged separately over Northern and Southern Africa, reflect the spatial and temporal variability of biomass burning events in agreement with the global chemical transport model TM5.

In this work we present an extensive sensitivity study of retrieved total ozone columns from clear sky Global Ozone Monitoring Experiment 2 (GOME-2) measurements between 325 and 335nm which are corrected for instrument degradation. Employing an algorithm based on the scaling of a reference ozone profile with the extension to analytically calculate total column averaging kernels, allows us to investigate the impact of the choice of the reference profile on the retrieved total ozone column, since it represents a regularization of the retrieval. It introduces an error to the retrieved column with respect to the true column typically in the order of 1% depending on the reference scaling profile. However, a proper interpretation of the retrieved column using the total column averaging kernel avoids this error, which is demonstrated by a validation of GOME-2 total ozone columns with collocated ozonesonde and ground-based total ozone column measurements. Globally, we report a bias of 0.1% and a SD of 2.5% for 647 collocations with ground-based and ozonesonde measurements at different geolocations in the period of 2007 to 2010. Futhermore, an extended validation solely based on ground-based observations and a strict cloud filtering shows that the use of pseudo spherical scalar radiative transfer is fully sufficient for the purpose of this retrieval. Polarization of light by atmospheric scattering affects the retrieval accuracy only marginally and thus can be ignored. Finally, we study the effect of instrument degradation on the retrieved total ozone columns for the first four years of GOME-2 observations and discuss the efficiency of the proposed radiometric correction.

Trends in the CO and C2H6 partial columns (~0–15 km) have been estimated from four European ground-based solar FTIR stations for the 1996–2006 time period. The CO trends from the four stations Jungfraujoch, Zugspitze, Harestua and Kiruna have been estimated to −0.45±0.16 % yr−1, −1.00±0.24 % yr−1, −0.62±0.19 % yr−1 and −0.61±0.16 % yr−1, respectively. The corresponding trends for C2H6 are −1.51±0.23 % yr−1, −2.11±0.30 % yr−1, −1.09±0.25 % yr−1 and −1.14±0.18 % yr−1. To find possible reasons for the CO trends, the global-scale EMEP MSC-W chemical transport model has been used in a series of sensitivity scenarios. It is shown that the trends are consistent with the combination of a 20 % decrease in the anthropogenic CO emissions seen in Europe and North America during the 1996-2006 period and a 20 % increase in the anthropogenic CO emissions in East Asia, during the same time period. The possible impacts of CH4 and biogenic volatile organic compounds (BVOCs) are also considered. The European and global-scale EMEP model have been evaluated against the measured CO and C2H6 partial columns from Jungfraujoch, Zugspitze, Bremen, Harestua, Kiruna and Ny-Ålesund. The European model reproduces, on average the measurements at the different sites fairly well and within 10–22 % deviation for CO and 14–31 % deviation for C2H6. Their seasonal amplitude is captured within 6–35 % and 9–124 % for CO and C2H6, respectively. However, 61–98 % of the CO and C26 partial columns in the European model are shown to arise from the boundary conditions, making the global-scale model a more suitable alternative when modeling theses two species. In the evaluation of the global model the average partial columns for year 2006 have shown to be within 1–9 % and 37–50 % for CO and C26, respectively. The global model sensitivity for assumptions done in this paper is also analyzed.

We present an intercomparison of three years of measurements of integrated water vapor (IWV) performed by the mid-infrared solar FTIR (Fourier Transform Infra-Red) instrument on the summit of Mt. Zugspitze (2964 m a.s.l.) and by the nearby near-infrared differential absorption lidar (DIAL) at the Schneefernerhaus research station (2675 m a.s.l.). The solar FTIR was shown to be one of the most accurate and precise IWV sounders in recent work (Sussmann et al., 2009) and is taken as the reference here. By calculating the FTIR-DIAL correlation (22 min coincidence interval, 15 min integration time) we derive an almost ideal slope of 0.996 (10), a correlation coefficient of R = 0.99, an IWV intercept of −0.039 (42) mm (−1.2 % of the mean), and a bias of −0.052 (26) mm (−1.6 % of the mean) from the scatter plot. By selecting a subset of coincidences with an optimum temporal and spatial matching between DIAL and FTIR, we obtain a conservative estimate of the precision of the DIAL in measuring IWV which is better than 0.1 mm (3.2 % of the mean). We found that for a temporal coincidence interval of 22 min the difference in IWV measured by these two systems is dominated by the volume mismatch (horizontal distance: 680 m). The outcome from this paper is twofold: (1) the IWV soundings by FTIR and DIAL agree very well in spite of the differing wavelength regions with different spectroscopic line parameters and retrieval algorithms used. (2) In order to derive an estimate of the precision of state-of-the-art IWV sounders from intercomparison experiments, it is necessary to use a temporal matching on time scales shorter than 10 min and a spatial matching on the 100-m scale.

This paper presents a validation study of SCIAMACHY CO total column measurements from the IMLM algorithm using ground-based spectrometer observations from twenty surface stations for the five year time period of 2003–2007. Overall we find a good agreement between SCIAMACHY and ground-based observations for both mean values as well as seasonal variations. For high-latitude Northern Hemisphere stations absolute differences between SCIAMACHY and ground-based measurements are close to or fall within the SCIAMACHY CO 2σ precision of 0.2×1018 molecules/cm2 (~10%) indicating that SCIAMACHY can observe CO accurately at high Northern Hemisphere latitudes. For Northern Hemisphere mid-latitude stations the validation is complicated due to the vicinity of emission sources for almost all stations, leading to higher ground-based measurements compared to SCIAMACHY CO within its typical sampling area of 8×8°. Comparisons with Northern Hemisphere mountain stations are hampered by elevation effects. After accounting for these effects, the validation provides satisfactory results. At Southern Hemisphere mid- to high latitudes SCIAMACHY is systematically lower than the ground-based measurements for 2003 and 2004, but for 2005 and later years the differences between SCIAMACHY and ground-based measurements fall within the SCIAMACHY precision. The 2003–2004 bias is consistent with a previously reported Southern Hemisphere bias based on comparisons with MOPITT CO and is currently under investigation. No other systematic spatial or temporal biases could be identified based on the validation presented in this paper. Validation results are robust with regard to the choices of the instrument-noise error filter, sampling area, and time averaging required for the validation of SCIAMACHY CO total column measurements. Finally, our results show that the spatial coverage of the ground-based measurements available for the validation of the 2003–2007 SCIAMACHY CO columns is sub-optimal for validation purposes, and that the recent and ongoing expansion of the ground-based network by carefully selecting new locations may be very beneficial for SCIAMACHY CO and other satellite trace gas measurements validation efforts.

This paper presents a validation study of SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) carbon monoxide (CO) total column measurements from the Iterative Maximum Likelihood Method (IMLM) algorithm using ground-based spectrometer observations from twenty surface stations for the five year time period of 2003–2007. Overall we find a good agreement between SCIAMACHY and ground-based observations for both mean values as well as seasonal variations. For high-latitude Northern Hemisphere stations absolute differences between SCIAMACHY and ground-based measurements are close to or fall within the SCIAMACHY CO 2σ precision of 0.2 × 1018 molecules/cm2 (∼10%) indicating that SCIAMACHY can observe CO accurately at high Northern Hemisphere latitudes. For Northern Hemisphere mid-latitude stations the validation is complicated due to the vicinity of emission sources for almost all stations, leading to higher ground-based measurements compared to SCIAMACHY CO within its typical sampling area of 8° × 8°. Comparisons with Northern Hemisphere mountain stations are hampered by elevation effects. After accounting for these effects, the validation provides satisfactory results. At Southern Hemisphere mid- to high latitudes SCIAMACHY is systematically lower than the ground-based measurements for 2003 and 2004, but for 2005 and later years the differences between SCIAMACHY and ground-based measurements fall within the SCIAMACHY precision. The 2003–2004 bias is consistent with previously reported results although its origin remains under investigation. No other systematic spatial or temporal biases could be identified based on the validation presented in this paper. Validation results are robust with regard to the choices of the instrument-noise error filter, sampling area, and time averaging required for the validation of SCIAMACHY CO total column measurements. Finally, our results show that the spatial coverage of the ground-based measurements available for the validation of the 2003–2007 SCIAMACHY CO columns is sub-optimal for validation purposes, and that the recent and ongoing expansion of the ground-based network by carefully selecting new locations may be very beneficial for SCIAMACHY CO and other satellite trace gas measurements validation efforts.

We present a method for harmonized retrieval of integrated water vapor (IWV) trends from existing, long-term, measurement records at the ground-based mid-infrared solar FTIR spectrometry stations of the Network for the Detection of Atmospheric Composition Change (NDACC). Correlation of IWV from FTIR with radiosondes shows an ideal slope of 1.00(3). This optimum matching is achieved via tuning one FTIR retrieval parameter, i.e., the strength of a Tikhonov regularization constraining the derivative (with respect to height) of retrieved water profiles given in per cent difference relative to an a priori profile. All other FTIR-sonde correlation parameters (intercept =0.02(12) mm, bias =0.02(5) mm, standard deviation of coincident IWV differences (stdv)=0.27 mm, R=0.99) are comparable to or better than results for all other ground-based IWV sounding techniques given in the literature. An FTIR-FTIR side-by-side intercomparison reveals a strong exponential increase in stdv as a function of increasing temporal mismatch starting at Δt ~1 min. This is due to atmospheric water vapor variability. Based on this result we derive an upper limit for the precision of the FTIR IWV retrieval for the smallest Δt(=3.75 min) still giving a statistically sufficient sample (32 coincidences), i.e., precision (IWVFTIR)

We present a method for harmonized retrieval of integrated water vapor (IWV) from existing, long-term, measurement records at the ground-based mid-infrared solar FTIR spectrometry stations of the Network for the Detection of Atmospheric Composition Change (NDACC). Correlation of IWV from FTIR with radiosondes shows an ideal slope of 1.00(3). This optimum matching is achieved via tuning one FTIR retrieval parameter, i.e., the strength of a Tikhonov regularization constraining the derivative (with respect to height) of retrieved water profiles given in per cent difference relative to an a priori profile. All other FTIR-sonde correlation parameters (intercept=0.02(12) mm, bias=0.02(5) mm, standard deviation of coincident IWV differences (stdv)=0.27 mm, R=0.99) are comparable to or better than results for all other ground-based IWV sounding techniques given in the literature. An FTIR-FTIR side-by-side intercomparison reveals a strong exponential increase in stdv as a function of increasing temporal mismatch starting at Δt≈1 min. This is due to atmospheric water vapor variability. Based on this result we derive an upper limit for the precision of the FTIR IWV retrieval for the smallest Δt(=3.75 min) still giving a statistically sufficient sample (32 coincidences), i.e., precision(IWVFTIR)

This paper presents extensive validation analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. The ACE satellite instruments operate in the mid-infrared and ultraviolet-visible-near-infrared spectral regions using the solar occultation technique. In order to continue the long-standing record of solar occultation measurements from space, a detailed quality assessment is required to evaluate the ACE data and validate their use for scientific purposes. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from satellite-borne, airborne, balloon-borne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the mean differences range generally between 0 and +10% with a slight but systematic positive bias (typically +5%). At higher altitudes (45–60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments by up to ~40% (typically +20%). For the ACE-MAESTRO version 1.2 ozone data product, agreement within ±10% (generally better than ±5%) is found between 18 and 40 km for the sunrise and sunset measurements. At higher altitudes (45–55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (by as much as −10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS and indicate a large positive bias (+10 to +30%) in this altitude range. In contrast, there is no significant difference in bias found for the ACE-FTS sunrise and sunset measurements. These systematic effects in the ozone profiles retrieved from the measurements of ACE-FTS and ACE-MAESTRO are being investigated. This work shows that the ACE instruments provide reliable, high quality measurements from the tropopause to the upper stratosphere and can be used with confidence in this vertical domain.

Classical error analysis in remote sounding distinguishes between four classes: "smoothing errors," "model parameter errors," "forward model errors," and "retrieval noise errors". For infrared sounding "interference errors", which, in general, cannot be described by these four terms, can be significant. Interference errors originate from spectral residuals due to "interfering species" whose spectral features overlap with the signatures of the target species. A general method for quantification of interference errors is presented, which covers all possible algorithmic implementations, i.e., fine-grid retrievals of the interfering species or coarse-grid retrievals, and cases where the interfering species are not retrieved. In classical retrieval setups interference errors can exceed smoothing errors and can vary by orders of magnitude due to state dependency. An optimum strategy is suggested which practically eliminates interference errors by systematically minimizing the regularization strength applied to joint profile retrieval of the interfering species. This leads to an interfering-species selective deweighting of the retrieval. Details of microwindow selection are no longer critical for this optimum retrieval and widened microwindows even lead to reduced overall (smoothing and interference) errors. Since computational power will increase, more and more operational algorithms will be able to utilize this optimum strategy in the future. The findings of this paper can be applied to soundings of all infrared-active atmospheric species, which include more than two dozen different gases relevant to climate and ozone. This holds for all kinds of infrared remote sounding systems, i.e., retrievals from ground-based, balloon-borne, airborne, or satellite spectroradiometers.

More and more profiles of atmospheric state parameters are being retrieved from remote soundings in the infrared spectral domain. Classical error analysis, which was originally applied to microwave sounding systems, distinguishes between "smoothing errors," "forward model errors," "forward model parameter errors," and "retrieval noise errors". We show that for infrared soundings "interference errors", which have not been treated up to now, can be significant. Interference errors originate from "interfering species" that introduce signatures into the spectral measurement which overlap with the spectral features used for retrieval of the target species. This is a frequent situation in infrared atmospheric spectra where the vibration-rotation bands of different species often overlap; it is not the case in the microwave region. This paper presents a full theoretical formulation of interference errors. It requires a generalized state vector including profile entries for all interfering species. This leads to a generalized averaging kernel matrix made up of classical averaging kernels plus here defined "interference kernels". The latter are used together with climatological covariances for the profiles of the interfering species in order to quantify the interference errors. To illustrate the methods we apply them to a real sounding and show that interference errors have a significant impact on standard CO profile retrievals from ground-based mid-infrared solar absorption spectra. We also demonstrate how to minimize overall error, which is a trade-off between minimizing interference errors and the smoothing error. The approach used in this paper can be applied to soundings of all infrared-active atmospheric species, which includes more than two dozen different gases relevant to climate and ozone. And this holds for all kind of infrared remote sounding systems, i.e., retrievals from ground-based, balloon-borne, airborne, or satellite spectroradiometers.