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Optical probes are frequently used for the detection of microphysical cloud particle properties such as liquid and ice phase, size and morphology. These properties can eventually influence the angular light scattering properties of cirrus clouds as well as the growth and accretion mechanisms of single cloud particles. In this study we compare four commonly used optical probes to examine their response to small cloud particles of different phase and asphericity. Cloud simulation experiments were conducted at the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at European Organisation for Nuclear Research (CERN). The chamber was operated in a series of multi-step adiabatic expansions to produce growth and sublimation of ice particles at super- and subsaturated ice conditions and for initial temperatures of −30, −40 and −50 °C. The experiments were performed for ice cloud formation via homogeneous ice nucleation. We report the optical observations of small ice particles in deep convection and in situ cirrus simulations. Ice crystal asphericity deduced from measurements of spatially resolved single particle light scattering patterns by the Particle Phase Discriminator mark 2 (PPD-2K, Karlsruhe edition) were compared with Cloud and Aerosol Spectrometer with Polarisation (CASPOL) measurements and image roundness captured by the 3View Cloud Particle Imager (3V-CPI). Averaged path light scattering properties of the simulated ice clouds were measured using the Scattering Intensity Measurements for the Optical detectioN of icE (SIMONE) and single particle scattering properties were measured by the CASPOL. We show the ambiguity of several optical measurements in ice fraction determination of homogeneously frozen ice in the case where sublimating quasi-spherical ice particles are present. Moreover, most of the instruments have difficulties of producing reliable ice fraction if small aspherical ice particles are present, and all of the instruments cannot separate perfectly spherical ice particles from supercooled droplets. Correlation analysis of bulk averaged path depolarisation measurements and single particle measurements of these clouds showed higher R2 values at high concentrations and small diameters, but these results require further confirmation. We find that none of these instruments were able to determine unambiguously the phase of the small particles. These results have implications for the interpretation of atmospheric measurements and parametrisations for modelling, particularly for low particle number concentration clouds.

The Optical Spectrograph and Infra-Red Imager System (OSIRIS) and the Atmospheric Chemistry Experiment (ACE) have been taking measurements from space since 2001 and 2003, respectively. This paper presents intercomparisons between ozone and NO2 measured by the ACE and OSIRIS satellite instruments and by ground-based instruments at the Polar Environment Atmospheric Research Laboratory (PEARL), which is located at Eureka, Canada (80° N, 86° W) and is operated by the Canadian Network for the Detection of Atmospheric Change (CANDAC). The ground-based instruments included in this study are four zenith-sky differential optical absorption spectroscopy (DOAS) instruments, one Bruker Fourier transform infrared spectrometer (FTIR) and four Brewer spectrophotometers. Ozone total columns measured by the DOAS instruments were retrieved using new Network for the Detection of Atmospheric Composition Change (NDACC) guidelines and agree to within 3.2%. The DOAS ozone columns agree with the Brewer spectrophotometers with mean relative differences that are smaller than 1.5%. This suggests that for these instruments the new NDACC data guidelines were successful in producing a homogenous and accurate ozone dataset at 80° N. Satellite 14–52 km ozone and 17–40 km NO2 partial columns within 500 km of PEARL were calculated for ACE-FTS Version 2.2 (v2.2) plus updates, ACE-FTS v3.0, ACE-MAESTRO (Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation) v1.2 and OSIRIS SaskMART v5.0x ozone and Optimal Estimation v3.0 NO2 data products. The new ACE-FTS v3.0 and the validated ACE-FTS v2.2 partial columns are nearly identical, with mean relative differences of 0.0 ± 0.2% and −0.2 ± 0.1% for v2.2 minus v3.0 ozone and NO2, respectively. Ozone columns were constructed from 14–52 km satellite and 0–14 km ozonesonde partial columns and compared with the ground-based total column measurements. The satellite-plus-sonde measurements agree with the ground-based ozone total columns with mean relative differences of 0.1–7.3%. For NO2, partial columns from 17 km upward were scaled to noon using a photochemical model. Mean relative differences between OSIRIS, ACE-FTS and ground-based NO2 measurements do not exceed 20%. ACE-MAESTRO measures more NO2 than the other instruments, with mean relative differences of 25–52%. Seasonal variation in the differences between NO2 partial columns is observed, suggesting that there are systematic errors in the measurements and/or the photochemical model corrections. For ozone spring-time measurements, additional coincidence criteria based on stratospheric temperature and the location of the polar vortex were found to improve agreement between some of the instruments. For ACE-FTS v2.2 minus Bruker FTIR, the 2007–2009 spring-time mean relative difference improved from −5.0 ± 0.4% to −3.1 ± 0.8% with the dynamical selection criteria. This was the largest improvement, likely because both instruments measure direct sunlight and therefore have well-characterized lines-of-sight compared with scattered sunlight measurements. For NO2, the addition of a ±1° latitude coincidence criterion improved spring-time intercomparison results, likely due to the sharp latitudinal gradient of NO2 during polar sunrise. The differences between satellite and ground-based measurements do not show any obvious trends over the missions, indicating that both the ACE and OSIRIS instruments continue to perform well.

This study investigates the long-term evolution of subtropical ozone profile time series (1999–2010) obtained from ground-based FTIR (Fourier Transform InfraRed) spectrometry at the Izaña Observatory ozone super-site. Different ozone retrieval strategies are examined, analysing the influence of an additional temperature retrieval and different constraints. The theoretical assessment reveals that the FTIR system is able to resolve four independent ozone layers with a precision of better than 6% in the troposphere and of better than 3% in the lower, middle and upper stratosphere. This total error includes the smoothing error, which dominates the random error budget. Furthermore, we estimate that the measurement noise as well as uncertainties in the applied atmospheric temperature profiles and instrumental line shape are leading error sources. We show that a simultaneous temperature retrieval can significantly reduce the total random errors and that a regular determination of the instrumental line shape is important for producing a consistent long-term dataset. These theoretical precision estimates are empirically confirmed by daily intercomparisons with Electro Chemical Cell (ECC) sonde profiles. In order to empirically document the long-term stability of the FTIR ozone profile data we compare the linear trends and seasonal cycles as obtained from the FTIR and ECC time series. Concerning seasonality, in winter both techniques observe stratospheric ozone profiles that are typical middle latitude profiles (low tropopause, low ozone maximum concentrations) and in summer/autumn profiles that are typical tropical profiles (high tropopause, high maximum concentrations). The linear trends estimated from the FTIR and the ECC datasets agree within their error bars. For the FTIR time series, we observe a significant negative trend in the upper troposphere/lower stratosphere of about −0.2% yr−1 and a significant positive trend in the middle and upper stratosphere of about +0.3% yr−1 and +0.4% yr−1, respectively. Identifying such small trends is a difficult task for any measurement technique. In this context, super-sites applying different techniques are very important for the detection of reliable ozone trends.

During the last decade, several limb sounding satellites have measured the global sodium (Na) number densities in the mesosphere and lower thermosphere (MLT). Datasets are now available from Global Ozone Monitoring by Occultation of Stars (GOMOS), the SCanning Imaging Absorption spectroMeter for Atmospheric CHartography (SCIAMACHY) (both on Envisat) and the Optical Spectrograph and InfraRed Imager System (OSIRIS) (on Odin). Furthermore, global model simulations of the Na layer in the MLT simulated by the Whole Atmosphere Community Climate Model, including the Na species (WACCM-Na), are available. In this paper, we compare these global datasets.The observed and simulated monthly averages of Na vertical column densities agree reasonably well with each other. They show a clear seasonal cycle with a summer minimum most pronounced at the poles. They also show signs of a semi-annual oscillation in the equatorial region. The vertical column densities vary from 0. 5 × 109 to 7 × 109 cm−2 near the poles and from 3 × 109 to 4 × 109 cm−2 at the Equator. The phase of the seasonal cycle and semi-annual oscillation shows small differences between the Na amounts retrieved from different instruments. The full width at half maximum of the profiles is 10 to 16 km for most latitudes, but significantly smaller in the polar summer. The centroid altitudes of the measured sodium profiles range from 89 to 95 km, whereas the model shows on average 2 to 4 km lower centroid altitudes. This may be explained by the mesopause being 3 km lower in the WACCM simulations than in measurements. Despite this global 2–4 km shift, the model captures well the latitudinal and temporal variations. The variation of the WACCM dataset during the year at different latitudes is similar to the one of the measurements. Furthermore, the differences between the measured profiles with different instruments and therefore different local times (LTs) are also present in the model-simulated profiles. This capturing of latitudinal and temporal variations is also found for the vertical column densities and profile widths.

Improving measurements of water vapour in the upper troposphere and lower stratosphere (UTLS) is a priority for the atmospheric science community. In this work, UTLS water vapour profiles derived from Atmospheric Chemistry Experiment (ACE) satellite measurements are assessed with coincident ground-based measurements taken at a high Arctic observatory at Eureka, Nunavut, Canada. Additional comparisons to satellite measurements taken by the Atmospheric Infrared Sounder (AIRS), Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), Microwave Limb Sounder (MLS), Scanning Imaging Absorption Spectrometer for Atmospheric CHartography (SCIAMACHY), and Tropospheric Emission Spectrometer (TES) are included to put the ACE Fourier transform spectrometer (ACE-FTS) and ACE Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) results in context. Measurements of water vapour profiles at Eureka are made using a Bruker 125HR solar absorption Fourier transform infrared spectrometer at the Polar Environment Atmospheric Research Laboratory (PEARL) and radiosondes launched from the Eureka Weather Station. Radiosonde measurements used in this study were processed with software developed by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) to account for known biases and calculate uncertainties in a well-documented and consistent manner. ACE-FTS measurements were within 11 ppmv (parts per million by volume; 13 %) of 125HR measurements between 6 and 14 km. Between 8 and 14 km ACE-FTS profiles showed a small wet bias of approximately 8 % relative to the 125HR. ACE-FTS water vapour profiles had mean differences of 13 ppmv (32 %) or better when compared to coincident radiosonde profiles at altitudes between 6 and 14 km; mean differences were within 6 ppmv (12 %) between 7 and 11 km. ACE-MAESTRO profiles showed a small dry bias relative to the 125HR of approximately 7 % between 6 and 9 km and 10 % between 10 and 14 km. ACE-MAESTRO profiles agreed within 30 ppmv (36 %) of the radiosondes between 7 and 14 km. ACE-FTS and ACE-MAESTRO comparison results show closer agreement with the radiosondes and PEARL 125HR overall than other satellite datasets – except for AIRS. Close agreement was observed between AIRS and the 125HR and radiosonde measurements, with mean differences within 5 % and correlation coefficients above 0.83 in the troposphere between 1 and 7 km. Comparisons to MLS at altitudes around 10 km showed a dry bias, e.g. mean differences between MLS and radiosondes were −25.6 %. SCIAMACHY comparisons were very limited due to minimal overlap between the vertical extent of the measurements. TES had no temporal overlap with the radiosonde dataset used in this study. Comparisons between TES and the 125HR showed a wet bias of approximately 25 % in the UTLS and mean differences within 14 % below 5 km.

Measurements of dry air mole fractions of atmospheric greenhouse gases are used in inverse models of atmospheric tracer transport to quantify their sources and sinks. The measurements have to be calibrated to a common scale to avoid bias in the inferred fluxes. For this purpose, the World Meteorological Organization (WMO) has set requirements for the interlaboratory compatibility of atmospheric greenhouse gas (GHG) measurements. A widely used series of devices for these measurements are the GHG analyzers manufactured by Picarro, Inc. These are often operated in humid air, and the effects of water vapor are corrected for in post-processing. Here, we report on rarely detected and previously unexplained biases of the water correction method for CO2 and CH4 in the literature. They are largest at water vapor mole fractions below 0.5 % H2O, which were undersampled in previous studies, and can therefore affect measurements obtained in humid air. Setups that dry sample air using Nafion membranes may be affected as well if there are differences in residual water vapor levels between sample and calibration air. The biases are caused by a sensitivity of the pressure in the measurement cavity to water vapor. We correct these biases by modifying the water correction method from the literature. Our method relies on experiments that maintain stable water vapor levels to allow equilibration of cavity pressure. In our experiments with the commonly used droplet method, this requirement was not fulfilled. Correcting CO2 measurements proved challenging, presumably because of our humidification method. Open questions pertain to differences among analyzers and variability over time. In our experiments, the biases amounted to considerable fractions of the WMO interlaboratory compatibility goals. Since measurements of dry air mole fractions of CO2 and CH4 are also subject to other uncertainties, correcting the cavity pressure-related biases helps keep the overall accuracy of measurements obtained with Picarro GHG analyzers in humid and potentially in Nafion-dried air within the WMO goals.

Reliable and reproducible measurements of atmospheric aerosol particle number size distributions below 10 nm require optimized classification instruments with high particle transmission efficiency. Almost all differential mobility analyzers (DMAs) have an unfavorable potential gradient at the outlet (e.g., long column, Vienna type) or at the inlet (nano-radial DMA), preventing them from achieving a good transmission efficiency for the smallest nanoparticles. We developed a new high-transmission inlet for the Caltech nano-radial DMA (nRDMA) that increases the transmission efficiency to 12 % for ions as small as 1.3 nm in Millikan–Fuchs mobility equivalent diameter, Dp (corresponding to 1.2 × 10−4 m2 V−1 s−1 in electrical mobility). We successfully deployed the nRDMA, equipped with the new inlet, in chamber measurements, using a particle size magnifier (PSM) and as a booster a condensation particle counter (CPC). With this setup, we were able to measure size distributions of ions within a mobility range from 1.2 × 10−4 to 5.8 × 10−6 m2 V−1 s−1. The system was modeled, tested in the laboratory and used to measure negative ions at ambient concentrations in the CLOUD (Cosmics Leaving Outdoor Droplets) 7 measurement campaign at CERN. We achieved a higher size resolution (R = 5.5 at Dp = 1.47 nm) than techniques currently used in field measurements (e.g., Neutral cluster and Air Ion Spectrometer (NAIS), which has a R ∼ 2 at largest sizes, and R ∼ 1.8 at Dp = 1.5 nm) and maintained a good total transmission efficiency (6.3 % at Dp = 1.5 nm) at moderate inlet and sheath airflows (2.5 and 30 L min−1, respectively). In this paper, by measuring size distributions at high size resolution down to 1.3 nm, we extend the limit of the current technology. The current setup is limited to ion measurements. However, we envision that future research focused on the charging mechanisms could extend the technique to measure neutral aerosol particles as well, so that it will be possible to measure size distributions of ambient aerosols from 1 nm to 1 µm.

An evaluation of the performance and relative accuracy of a Cavity Attenuated Phase-Shift Single Scattering Albedo Monitor (CAPS PMSSA; Aerodyne Research, Inc.) was conducted in an optical-closure study with proven technologies: Cavity Attenuated Phase-Shift Particle Extinction Monitor (CAPS PMex; Aerodyne Research, Inc.), three-wavelength integrating nephelometer (TSI Model 3563) and three-wavelength filter-based Particle Soot Absorption Photometer (PSAP; Radiance Research Inc.). The evaluation was conducted by connecting the instruments to a controlled aerosol generation system and comparing the measured scattering, extinction and absorption coefficients measured by the CAPS PMSSA with the independent measurements. Three different particle types were used to generate aerosol samples with single-scattering albedos (SSAs) ranging from 0.4 to 1.0 at 630 nm wavelength. The CAPS PMSSA measurements compared well with the proven technologies. Extinction measurement comparisons exhibited a slope of the linear regression line for the full dataset between 1.05 and 1.01, an intercept below ±1.5×10-6 m−1 (±1.5 Mm−1), and a regression coefficient R2>0.99, whereas scattering measurements had a slope between 0.90 and 1.04, an intercept of less than ±2.0×10-6 m−1 (2.0 Mm−1), and a coefficient R2>0.96. The derived CAPS PMSSA absorption compared well to the PSAP measurements for the small particle sizes and modest (0.4 to 0.6) SSA values tested, with a linear regression slope between 0.90 and 1.07, an intercept of ±3.0×10-6 m−1 (3.0 Mm−1), and a coefficient R2>0.99. For the SSA measurements, agreement was highest (regression slopes within 1 %) for SSA =1.0 particles at extinction levels of per tens of inverse megameters and above; however, as extinctions approach 0, small uncertainties in the baseline can introduce larger errors. SSA measurements for absorbing particles exhibited absolute differences up to 18 %, though it is not clear which measurement had the best relative accuracy. For a given particle type, the CAPS PMSSA instrument exhibited the lowest scatter around the average. This study demonstrates that the CAPS PMSSA is a robust and reliable instrument for the direct measurement of the scattering and extinction coefficients and thus SSA. This conclusion also holds for the indirect measurement of the absorption coefficient with the constraint that the relative accuracy of this particular determination degrades as the SSA and particle size increases.

The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) has shown that the sensor IASI aboard the satellite MetOp can measure the free tropospheric {H2O,δD} pair distribution twice per day on a quasi-global scale. Such data are very promising for investigating tropospheric moisture pathways, however, the complex data characteristics compromise their usage in the context of model evaluation studies. Here we present a tool that allows for simulating MUSICA MetOp/IASI {H2O,δD} pair remote sensing data for a given model atmosphere, thereby creating model data that have the remote sensing data characteristics assimilated. This model data can then be compared to the MUSICA data. The retrieval simulation method is based on the physical principles of radiative transfer and we show that the uncertainty of the simulations is within the uncertainty of the MUSICA MetOp/IASI products, i.e. the retrieval simulations are reliable enough. We demonstrate the working principle of the simulator by applying it to ECHAM5-wiso model data. The few case studies clearly reveal the large potential of the MUSICA MetOp/IASI {H2O,δD} data pairs for evaluating modelled moisture pathways. The tool is made freely available in form of MATLAB and Python routines and can be easily connected to any atmospheric water vapour isotopologue model.

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‰.