Observations Of Polar Stratospheric Clouds Research Articles

Polar Stratospheric Cloud Observations at Concordia Station by Remotely Controlled Lidar Observatory

Polar stratospheric clouds (PSCs) form in polar regions, typically between 15 and 25 km above mean sea level, when the local temperature is sufficiently low. PSCs play an important role in the ozone chemistry and the dehydration and denitrification of the stratosphere. Lidars with a depolarization channel may be used to detect and classify different classes of PSCs. The main PSC classes are water ice, nitric acid trihydrate (NAT), and supercooled ternary solutions (STSs), the latter being liquid droplets consisting of water, nitric acid, and sulfuric acid. PSCs have been observed at the lidar observatory at Concordia Station from 2014 onward. The harsh environmental conditions at Concordia during winter render successful lidar operation difficult. To facilitate the operation of the observatory, several measures have been put in place to achieve an almost complete remote control of the system. PSC occurrence is strongly correlated with local temperatures and is affected by dynamics, as the PSC coverage during the observation season shows. PSC observations in 2021 are shown as an example of the capability and functionality of the lidar observatory. A comparison of the observations with the satellite-borne CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar has been made to demonstrate the quality of the data and their representativeness for the Antarctic Plateau.

Statistical analysis of observations of polar stratospheric clouds with a lidar in Kiruna, northern Sweden

Abstract. In the present paper, we analyse 11 years of lidar measurements to derive general characteristics of polar stratospheric clouds (PSCs) and to examine how mountain lee waves influence PSC properties. Measurements of PSCs were made with a backscatter lidar located in Kiruna, northern Sweden, in the lee of the Scandinavian mountain range. The statistical analysis demonstrates that nearly half of all observed PSCs consisted of nitric acid trihydrate (NAT) particles, while ice clouds accounted for only a small fraction, and the remainder consisted of supercooled ternary solution (STS) and mixtures of different compositions. Most PSCs were observed around 22 km altitude. Mountain lee waves provide a distinct influence on PSC chemical composition and cloud height distribution. Ice PSCs were about 5 times as frequent, and NAT clouds were about half as frequent under wave conditions. PSCs were on average at 2 km higher altitudes when under the influence of mountain lee waves.

OClO as observed by TROPOMI: a comparison with meteorological parameters and polar stratospheric cloud observations

Abstract. Chlorine dioxide (OClO) is a by-product of the ozone-depleting halogen chemistry in the stratosphere. Although it is rapidly photolysed at low solar zenith angles (SZAs), it plays an important role as an indicator of the chlorine activation in polar regions during polar winter and spring at twilight conditions because of the nearly linear dependence of its formation on chlorine oxide (ClO). Here, we compare slant column densities (SCDs) of chlorine dioxide (OClO) retrieved by means of differential optical absorption spectroscopy (DOAS) from spectra measured by the TROPOspheric Monitoring Instrument (TROPOMI) with meteorological data for both Antarctic and Arctic regions for the first three winters in each of the hemispheres (November 2017–October 2020). TROPOMI, a UV–Vis–NIR–SWIR instrument on board of the Sentinel-5P satellite, monitors the Earth's atmosphere in a near-polar orbit at an unprecedented spatial resolution and signal-to-noise ratio and provides daily global coverage at the Equator and thus even more frequent observations at polar regions. The observed OClO SCDs are generally well correlated with the meteorological conditions in the polar winter stratosphere; for example, the chlorine activation signal appears as a sharp gradient in the time series of the OClO SCDs once the temperature drops to values well below the nitric acid trihydrate (NAT) existence temperature (TNAT). Also a relation of enhanced OClO values at lee sides of mountains can be observed at the beginning of the winters, indicating a possible effect of lee waves on chlorine activation. The dataset is also compared with CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) polar stratospheric cloud (PSC) observations. In general, OClO SCDs coincide well with CALIOP measurements for which PSCs are detected. Very high OClO levels are observed for the northern hemispheric winter 2019/20, with an extraordinarily long period with a stable polar vortex being even close to the values found for southern hemispheric winters. An extraordinary winter in the Southern Hemisphere was also observed in 2019, with a minor sudden stratospheric warming at the beginning of September. In this winter, similar OClO values were measured in comparison to the previous (usual) winter till that event but with a OClO deactivation that was 1–2 weeks earlier.

New Insights into Polar Stratospheric Clouds

New satellite observations of polar stratospheric clouds have advanced our understanding of how, when, and where they form, their composition, and their role in ozone depletion.

Polar Stratospheric Clouds Detection at Belgrano II Antarctic Station with Visible Ground-Based Spectroscopic Measurements

By studying the evolution of the color index (CI) during twilight at high latitudes, polar stratospheric clouds (PSCs) can be detected and characterized. In this work, this method has been applied to the measurements obtained by a visible ground-based spectrometer and PSCs have been studied over the Belgrano II Antarctic station for years 2018 and 2019. The methodology applied has been validated by full spherical radiative transfer simulations, which confirm that PSCs can be detected and their altitude estimated with this instrumentation. Moreover, our investigation shows that this method is useful even in presence of optically thin tropospheric clouds or aerosols. PSCs observed in this work have been classified by altitude. Our results are in good agreement with the stratospheric temperature evolution obtained by the global meteorological model ECMWF (European Centre for Medium Range Weather Forecasts) and with satellite PSCs observations from CALIPSO (Cloud-Aerosol-Lidar and Infrared Pathfinder Satellite Observations). To investigate the presence and long-term evolution of PSCs, the methodology used in this work could also be applied to foreseen and/or historical observations obtained with ground-based spectrometers such e. g. those dedicated to Differential Optical Absorption Spectroscopy (DOAS) for trace gas observation in Arctic and Antarctic sites.

A new method to detect and classify polar stratospheric nitric acid trihydrate clouds derived from radiative transfer simulations and its first application to airborne infrared limb emission observations

Abstract. Polar stratospheric clouds (PSCs) play an important role in the spatial and temporal evolution of trace gases inside the polar vortex due to different processes, such as chlorine activation and NOy redistribution. As there are still uncertainties in the representation of PSCs in model simulations, detailed observations of PSCs and information on their type – nitric acid trihydrate (NAT), supercooled ternary solution (STS), and ice – are desirable. The measurements inside PSCs made by the CRISTA-NF (CRyogenic Infrared Spectrometers and Telescope for the Atmosphere – New Frontiers) airborne infrared limb sounder during the RECONCILE (Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interactions) aircraft campaign showed a spectral peak at about 816 cm−1. This peak is shifted compared with the known peak at about 820 cm−1, which is recognised as being caused by the emission of radiation by small NAT particles. To investigate the reason for this spectral difference, we performed a large set of radiative transfer simulations of infrared limb emission spectra in the presence of various PSCs (NAT, STS, ice, and mixtures) for the airborne viewing geometry of CRISTA-NF. NAT particles can cause different spectral features in the 810–820 cm−1 region. The simulation results show that the appearance of the feature changes with an increasing median radius of the NAT particle size distribution, from a peak at 820 cm−1 to a shifted peak and, finally, to a step-like feature in the spectrum, caused by the increasing contribution of scattering to the total extinction. Based on the appearance of the spectral feature, we defined different colour indices to detect PSCs containing NAT particles and to subgroup them into three size regimes under the assumption of spherical particles: small NAT (≤ 1.0 µm), medium NAT (1.5–4.0 µm), and large NAT (≥ 3.5 µm). Furthermore, we developed a method to detect the bottom altitude of a cloud by using the cloud index (CI), a colour ratio indicating the optical thickness, and the vertical gradient of the CI. Finally, we applied the methods to observations of the CRISTA-NF instrument during one local flight of the RECONCILE aircraft campaign and found STS and medium-sized NAT.

Quasi-coincident observations of polar stratospheric clouds by ground-based lidar and CALIOP at Concordia (Dome C, Antarctica) from 2014 to 2018

Abstract. Polar stratospheric clouds (PSCs) have been observed from 2014 to 2018 from the lidar observatory at the Antarctic Concordia station (Dome C), included as a primary station in the NDACC (Network for Detection of Atmospheric Climate Change). Many of these measurements have been performed in coincidence with overpasses of the satellite-borne CALIOP (Cloud Aerosol Lidar with Orthogonal Polarization) lidar, in order to perform a comparison in terms of PSC detection and composition classification. Good agreement has been obtained, despite intrinsic differences in observation geometry and data sampling. This study reports, to our knowledge, the most extensive comparison of PSC observations by ground-based and satellite-borne lidars. The PSCs observed by the ground-based lidar and CALIOP form a complementary and congruent dataset and allow us to study the seasonal and interannual variations in PSC occurrences at Dome C. Moreover, a strong correlation with the formation temperature of NAT (nitric acid trihydrate), TNAT, calculated from local temperature, pressure, and H2O and HNO3 concentrations is shown. PSCs appear at Dome C at the beginning of June up to 26 km and start to disappear in the second half of August, when the local temperatures start to rise above TNAT. Rare PSC observations in September coincide with colder air masses below 18 km.

On the best locations for ground-based polar stratospheric cloud (PSC) observations

Abstract. Spaceborne observations of polar stratospheric clouds (PSCs) with the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite provide a comprehensive picture of the occurrence of Arctic and Antarctic PSCs as well as their microphysical properties. However, advances in understanding PSC microphysics also require measurements with ground-based instruments, which are often superior to CALIOP in terms of, for example, time resolution, measured parameters, and signal-to-noise ratio. This advantage is balanced by the location of ground-based PSC observations and their dependence on tropospheric cloudiness. CALIPSO observations during the boreal winters from December 2006 to February 2018 and the austral winters 2012 and 2015 are used to assess the effect of tropospheric cloudiness and other measurement-inhibiting factors on the representativeness of ground-based PSC observations with lidar in the Arctic and Antarctic, respectively. Information on tropospheric and stratospheric clouds from the CALIPSO Cloud Profile product (05kmCPro version 4.10) and the CALIPSO polar stratospheric cloud mask version 2, respectively, is combined on a profile-by-profile basis to identify conditions under which a ground-based lidar is likely to perform useful measurements for the analysis of PSC occurrence. It is found that the location of a ground-based measurement together with the related tropospheric cloudiness can have a profound impact on the derived PSC statistics and that these findings are rarely in agreement with polewide results from CALIOP observations. Considering the current polar research infrastructure, it is concluded that the most suitable sites for the expansion of capabilities for ground-based lidar observations of PSCs are Summit and Villum in the Arctic and Mawson, Troll, and Vostok in the Antarctic.

OMPS LP Observations of PSC Variability During the NH 2019–2020 Season

AbstractSeasonal ozone depletion in the polar regions (during late winter and early spring) depends on the presence and distribution of polar stratospheric clouds (PSCs). In this paper, we present new satellite observations of PSCs by the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) instrument. LP cloud detections are identified as PSCs based on location, altitude, and background atmosphere temperature. The hyperspectral capabilities of OMPS LP enable PSC detection to occur concurrent with stratospheric ozone measurements from the same instrument. We present PSC results from the Northern Hemisphere 2019–2010 winter/spring season to illustrate the exceptional nature of this season. Future OMPS LP instruments flying on Joint Polar Satellite System (JPSS) satellites will continue PSC observations into the 2030s.

Exploration of machine learning methods for the classification of infrared limb spectra of polar stratospheric clouds

Abstract. Polar stratospheric clouds (PSCs) play a key role in polar ozone depletion in the stratosphere. Improved observations and continuous monitoring of PSCs can help to validate and improve chemistry–climate models that are used to predict the evolution of the polar ozone hole. In this paper, we explore the potential of applying machine learning (ML) methods to classify PSC observations of infrared limb sounders. Two datasets were considered in this study. The first dataset is a collection of infrared spectra captured in Northern Hemisphere winter 2006/2007 and Southern Hemisphere winter 2009 by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument on board the European Space Agency's (ESA) Envisat satellite. The second dataset is the cloud scenario database (CSDB) of simulated MIPAS spectra. We first performed an initial analysis to assess the basic characteristics of the CSDB and to decide which features to extract from it. Here, we focused on an approach using brightness temperature differences (BTDs). From both the measured and the simulated infrared spectra, more than 10 000 BTD features were generated. Next, we assessed the use of ML methods for the reduction of the dimensionality of this large feature space using principal component analysis (PCA) and kernel principal component analysis (KPCA) followed by a classification with the support vector machine (SVM). The random forest (RF) technique, which embeds the feature selection step, has also been used as a classifier. All methods were found to be suitable to retrieve information on the composition of PSCs. Of these, RF seems to be the most promising method, being less prone to overfitting and producing results that agree well with established results based on conventional classification methods.

Comparison of Antarctic polar stratospheric cloud observations by ground-based and space-borne lidar and relevance for chemistry–climate models

Abstract. A comparison of polar stratospheric cloud (PSC) occurrence from 2006 to 2010 is presented, as observed from the ground-based lidar station at McMurdo (Antarctica) and by the satellite-borne CALIOP lidar (Cloud-Aerosol Lidar with Orthogonal Polarization) measuring over McMurdo. McMurdo (Antarctica) is one of the primary lidar stations for aerosol measurements of the NDACC (Network for Detection of Atmospheric Climate Change). The ground-based observations have been classified with an algorithm derived from the recent v2 detection and classification scheme, used to classify PSCs observed by CALIOP. A statistical approach has been used to compare ground-based and satellite-based observations, since point-to-point comparison is often troublesome due to the intrinsic differences in the observation geometries and the imperfect overlap of the observed areas. A comparison of space-borne lidar observations and a selection of simulations obtained from chemistry–climate models (CCMs) has been made by using a series of quantitative diagnostics based on the statistical occurrence of different PSC types. The distribution of PSCs over Antarctica, calculated by several CCMVal-2 and CCMI chemistry–climate models has been compared with the PSC coverage observed by the satellite-borne CALIOP lidar. The use of several diagnostic tools, including the temperature dependence of the PSC occurrences, evidences the merits and flaws of the different models. The diagnostic methods have been defined to overcome (at least partially) the possible differences due to the resolution of the models and to identify differences due to microphysics (e.g., the dependence of PSC occurrence on T−TNAT). A significant temperature bias of most models has been observed, as well as a limited ability to reproduce the longitudinal variations in PSC occurrences observed by CALIOP. In particular, a strong temperature bias has been observed in CCMVal-2 models with a strong impact on PSC formation. The WACCM-CCMI (Whole Atmosphere Community Climate Model – Chemistry-Climate Model Initiative) model compares rather well with the CALIOP observations, although a temperature bias is still present.

Polar stratospheric cloud climatology based on CALIPSO spaceborne lidar measurements from 2006 to 2017

Abstract. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite has been observing polar stratospheric clouds (PSCs) from mid-June 2006 until the present. The spaceborne lidar profiles PSCs with unprecedented spatial (5 km horizontal×180 m vertical) resolution and its dual-polarization capability enables classification of PSCs according to composition. Nearly coincident Aura Microwave Limb Sounder (MLS) measurements of the primary PSC condensables (HNO3 and H2O) provide additional constraints on particle composition. A new CALIOP version 2 (v2) PSC detection and composition classification algorithm has been implemented that corrects known deficiencies in previous algorithms and includes additional refinements to improve composition discrimination. Major v2 enhancements include dynamic adjustment of composition boundaries to account for effects of denitrification and dehydration, explicit use of measurement uncertainties, addition of composition confidence indices, and retrieval of particulate backscatter, which enables simplified estimates of particulate surface area density (SAD) and volume density (VD). The over 11 years of CALIOP PSC observations in each v2 composition class conform to their expected thermodynamic existence regimes, which is consistent with previous analyses of data from 2006 to 2011 and underscores the robustness of the v2 composition discrimination approach. The v2 algorithm has been applied to the CALIOP dataset to produce a PSC reference data record spanning the 2006–2017 time period, which is the foundation for a new comprehensive, high-resolution climatology of PSC occurrence and composition for both the Antarctic and Arctic. Time series of daily-averaged, vortex-wide PSC areal coverage versus altitude illustrate that Antarctic PSC seasons are similar from year to year, with about 25 % relative standard deviation in Antarctic PSC spatial volume at the peak of the season in July and August. Multi-year average, monthly zonal mean cross sections depict the climatological patterns of Antarctic PSC occurrence in latitude–altitude and also equivalent-latitude–potential-temperature coordinate systems, with the latter system better capturing the microphysical processes controlling PSC existence. Polar maps of the multi-year mean geographical patterns in PSC occurrence frequency show a climatological maximum between longitudes 90∘ W and 0∘, which is the preferential region for forcing by orography and upper tropospheric anticyclones. The climatological mean distributions of particulate SAD and VD also show maxima in this region due to the large enhancements from the frequent ice clouds. Stronger wave activity in the Northern Hemisphere leads to a more disturbed Arctic polar vortex, whose evolution and lifetime vary significantly from year to year. Accordingly, Arctic PSC areal coverage is distinct from year to year with no “typical” year, and the relative standard deviation in Arctic PSC spatial volume is >100 % throughout most of the season. When PSCs are present in the Arctic, they most likely occur between longitudes 60∘ W and 90∘ E, which is consistent with the preferential location of the Arctic vortex. Comparisons of CALIOP v2 and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) Antarctic PSC observations show excellent correspondence in the overall spatial and temporal evolution, as well as for different PSC composition classes. Climatological patterns of CALIOP v2 PSC occurrence frequency in the vicinity of McMurdo Station, Antarctica, and Ny-Ålesund, Spitsbergen, are similar in nature to those derived from local ground-based lidar measurements. To investigate the possibility of longer-term trends, appropriately subsampled and averaged CALIOP v2 PSC observations from 2006 to 2017 were compared with PSC data during the 1978–1989 period obtained by the spaceborne solar occultation instrument SAM II (Stratospheric Aerosol Measurement II). There was good consistency between the two instruments in column Antarctic PSC occurrence frequency, suggesting that there has been no long-term trend. There was less overall consistency between the Arctic records, but it is very likely due to the high degree of interannual variability in PSCs rather than a long-term trend.

A climatology of polar stratospheric cloud composition between 2002 and 2012 based on MIPAS/Envisat observations

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument aboard the European Space Agency (ESA) Envisat satellite operated from July 2002 to April 2012. The infrared limb emission measurements provide a unique dataset of day and night observations of polar stratospheric clouds (PSCs) up to both poles. A recent classification method for PSC types in infrared (IR) limb spectra using spectral measurements in different atmospheric window regions has been applied to the complete mission period of MIPAS. The method uses a simple probabilistic classifier based on Bayes' theorem with a strong independence assumption on a combination of a well-established two-colour ratio method and multiple 2-D probability density functions of brightness temperature differences. The Bayesian classifier distinguishes between solid particles of ice, nitric acid trihydrate (NAT), and liquid droplets of supercooled ternary solution (STS), as well as mixed types. A climatology of MIPAS PSC occurrence and specific PSC classes has been compiled. Comparisons with results from the classification scheme of the spaceborne lidar Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol-Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite show excellent correspondence in the spatial and temporal evolution for the area of PSC coverage (APSC) even for each PSC class. Probability density functions of the PSC temperature, retrieved for each class with respect to equilibrium temperature of ice and based on coincident temperatures from meteorological reanalyses, are in accordance with the microphysical knowledge of the formation processes with respect to temperature for all three PSC types. This paper represents unprecedented pole-covering day- and nighttime climatology of the PSC distributions and their composition of different particle types. The dataset allows analyses on the temporal and spatial development of the PSC formation process over multiple winters. At first view, a more general comparison of APSC and AICE retrieved from the observations and from the existence temperature for NAT and ice particles based on the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis temperature data shows the high potential of the climatology for the validation and improvement of PSC schemes in chemical transport and chemistry–climate models.

Accuracy and precision of polar lower stratospheric temperatures from reanalyses evaluated from A-Train CALIOP and MLS, COSMIC GPS RO, and the equilibrium thermodynamics of supercooled ternary solutions and ice clouds

Abstract. We investigate the accuracy and precision of polar lower stratospheric temperatures (100–10 hPa during 2008–2013) reported in several contemporary reanalysis datasets comprising two versions of the Modern-Era Retrospective analysis for Research and Applications (MERRA and MERRA-2), the Japanese 55-year Reanalysis (JRA-55), the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-I), and the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (NCEP-CFSR). We also include the Goddard Earth Observing System model version 5.9.1 near-real-time analysis (GEOS-5.9.1). Comparisons of these datasets are made with respect to retrieved temperatures from the Aura Microwave Limb Sounder (MLS), Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) Global Positioning System (GPS) radio occultation (RO) temperatures, and independent absolute temperature references defined by the equilibrium thermodynamics of supercooled ternary solutions (STSs) and ice clouds. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations of polar stratospheric clouds are used to determine the cloud particle types within the Aura MLS geometric field of view. The thermodynamic calculations for STS and the ice frost point use the colocated MLS gas-phase measurements of HNO3 and H2O. The estimated bias and precision for the STS temperature reference, over the 68 to 21 hPa pressure range, are 0.6–1.5 and 0.3–0.6 K, respectively; for the ice temperature reference, they are 0.4 and 0.3 K, respectively. These uncertainties are smaller than those estimated for the retrieved MLS temperatures and also comparable to GPS RO uncertainties (bias < 0.2 K, precision > 0.7 K) in the same pressure range. We examine a case study of the time-varying temperature structure associated with layered ice clouds formed by orographic gravity waves forced by flow over the Palmer Peninsula and compare how the wave amplitudes are reproduced by each reanalysis dataset. We find that the spatial and temporal distribution of temperatures below the ice frost point, and hence the potential to form ice polar stratospheric clouds (PSCs) in model studies driven by the reanalyses, varies significantly because of the underlying differences in the representation of mountain wave activity. High-accuracy COSMIC temperatures are used as a common reference to intercompare the reanalysis temperatures. Over the 68–21 hPa pressure range, the biases of the reanalyses with respect to COSMIC temperatures for both polar regions fall within the narrow range of −0.6 K to +0.5 K. GEOS-5.9.1, MERRA, MERRA-2, and JRA-55 have predominantly cold biases, whereas ERA-I has a predominantly warm bias. NCEP-CFSR has a warm bias in the Arctic but becomes substantially colder in the Antarctic. Reanalysis temperatures are also compared with the PSC reference temperatures. Over the 68–21 hPa pressure range, the reanalysis temperature biases are in the range −1.6 to −0.3 K with standard deviations ∼ 0.6 K for the CALIOP STS reference, and in the range −0.9 to +0.1 K with standard deviations ∼ 0.7 K for the CALIOP ice reference. Comparisons of MLS temperatures with the PSC reference temperatures reveal vertical oscillations in the MLS temperatures and a significant low bias in MLS temperatures of up to 3 K.

A multi-wavelength classification method for polar stratospheric cloud types using infrared limb spectra

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument on board the ESA Envisat satellite operated from July 2002 until April 2012. The infrared limb emission measurements represent a unique dataset of daytime and night-time observations of polar stratospheric clouds (PSCs) up to both poles. Cloud detection sensitivity is comparable to space-borne lidars, and it is possible to classify different cloud types from the spectral measurements in different atmospheric windows regions. Here we present a new infrared PSC classification scheme based on the combination of a well-established two-colour ratio method and multiple 2-D brightness temperature difference probability density functions. The method is a simple probabilistic classifier based on Bayes' theorem with a strong independence assumption. The method has been tested in conjunction with a database of radiative transfer model calculations of realistic PSC particle size distributions, geometries, and composition. The Bayesian classifier distinguishes between solid particles of ice and nitric acid trihydrate (NAT), as well as liquid droplets of super-cooled ternary solution (STS). The classification results are compared to coincident measurements from the space-borne lidar Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument over the temporal overlap of both satellite missions (June 2006–March 2012). Both datasets show a good agreement for the specific PSC classes, although the viewing geometries and the vertical and horizontal resolution are quite different. Discrepancies are observed between the CALIOP and the MIPAS ice class. The Bayesian classifier for MIPAS identifies substantially more ice clouds in the Southern Hemisphere polar vortex than CALIOP. This disagreement is attributed in part to the difference in the sensitivity on mixed-type clouds. Ice seems to dominate the spectral behaviour in the limb infrared spectra and may cause an overestimation in ice occurrence compared to the real fraction of ice within the PSC area in the polar vortex. The entire MIPAS measurement period was processed with the new classification approach. Examples like the detection of the Antarctic NAT belt during early winter, and its possible link to mountain wave events over the Antarctic Peninsula, which are observed by the Atmospheric Infrared Sounder (AIRS) instrument, highlight the importance of a climatology of 9 Southern Hemisphere and 10 Northern Hemisphere winters in total. The new dataset is valuable both for detailed process studies, and for comparisons with and improvements of the PSC parameterizations used in chemistry transport and climate models.

Vortex-wide chlorine activation by a mesoscale PSC event in the Arctic winter of 2009/10

Abstract. In the Arctic polar vortex of the 2009/10 winter temperatures were low enough to allow widespread formation of polar stratospheric clouds (PSCs). These clouds occurred during the initial chlorine activation phase which provided the opportunity to investigate the impact of PSCs on chlorine activation. Satellite observations of gas-phase species and PSCs are used in combination with trajectory modeling to assess this initial activation. The initial activation occurred in association with the formation of PSCs over the east coast of Greenland at the beginning of January 2010. Although this area of PSCs covered only a small portion of the vortex, it was responsible for almost the entire initial activation of chlorine vortex wide. Observations show HCl (hydrochloric acid) mixing ratios decreased rapidly in and downstream of this region. Trajectory calculations and simplified heterogeneous chemistry modeling confirmed that the initial chlorine activation continued until ClONO2 (chlorine nitrate) was completely depleted and the activated air masses were advected throughout the polar vortex. For the calculation of heterogeneous reaction rates, surface area density is estimated from backscatter observations. Modeled heterogeneous reaction rates along trajectories intersecting with the PSCs indicate that the initial phase of chlorine activation occurred in just a few hours. These calculations also indicate that chlorine activation on the binary background aerosol is significantly slower than on the PSC particles and the observed chlorine activation can only be explained by an increase in surface area density due to PSC formation. Furthermore, there is a strong correlation between the magnitude of the observed HCl depletion and PSC surface area density.

Polar stratospheric cloud evolution and chlorine activation measured by CALIPSO and MLS, and modeled by ATLAS

Abstract. We examined observations of polar stratospheric clouds (PSCs) by CALIPSO, and of HCl and ClO by MLS along air mass trajectories, to investigate the dependence of the inferred PSC composition on the temperature history of the air parcels and the dependence of the level of chlorine activation on PSC composition. Several case studies based on individual trajectories from the Arctic winter 2009/2010 were conducted, with the trajectories chosen such that the first processing of the air mass by PSCs in this winter occurred on the trajectory. Transitions of PSC composition classes were observed to be highly dependent on the temperature history. In cases of a gradual temperature decrease, nitric acid trihydrate (NAT) and super-cooled ternary solution (STS) mixture clouds were observed. In cases of rapid temperature decrease, STS clouds were first observed, followed by NAT/STS mixture clouds. When temperatures dropped below the frost point, ice clouds formed and then transformed into NAT/STS mixture clouds when temperature increased above the frost point. The threshold temperature for rapid chlorine activation on PSCs is approximately 4 K below the NAT existence temperature, TNAT. Furthermore, simulations of the ATLAS chemistry and transport box model along the trajectories were used to corroborate the measurements and show good agreement with the observations. Rapid chlorine activation was observed when an air mass encountered PSCs. Usually, chlorine activation was limited by the amount of available ClONO2. Where ClONO2 was not the limiting factor, a large dependence on temperature was evident.

Observation of Polar Stratospheric Clouds over Antarctica Using Thermal Infrared Spectra Measured by TANSO-FTS/GOSAT

Observation of Polar Stratospheric Clouds over Antarctica Using Thermal Infrared Spectra Measured by TANSO-FTS/GOSAT

Observation of polar stratospheric clouds over Obninsk in December 2012

In late December 2012 a blocking anticyclone followed by the event of minor stratospheric warming, set in the troposphere over West Siberia and, after that, over the European part of Russia. As a result of the deformation of a polar stratospheric vortex, the temperature in the lower stratosphere over Obninsk dropped below the threshold of the formation of polar stratospheric clouds. The lidar measurements of temperature, ozone values, and aerosol characteristics in the middle atmosphere were carried out at the lidar station during this atmospheric event. In three cases, polar stratospheric clouds (PSCs) referred to NAT Ia type according to the sounding results, were registered at the height of about 20 km. No considerable decrease in the ozone concentration in the area of PSC formation was revealed in these measurements.

Assessing lidar‐based classification schemes for polar stratospheric clouds based on 16 years of measurements at Esrange, Sweden

AbstractLidar measurements of polar stratospheric clouds (PSCs) are commonly analyzed in classification schemes that apply the backscatter ratio and the particle depolarization ratio. This similarity of input data suggests comparable results of different classification schemes—despite measurements being performed with a variety of mostly custom‐made instruments. Based on a time series of 16 years of lidar measurements at Esrange (68°N, 21°E), Sweden, we show that PSC classification differs substantially depending on the applied scheme. The discrepancies result from varying threshold values of lidar‐derived parameters used to define certain PSC types. The resulting inconsistencies could impact the understanding of long‐term PSC observations documented in the literature. We identify two out of seven considered classification schemes that are most likely to give reliable results and should be used in future lidar‐based studies. Using polarized backscatter ratios gives the advantage of increased contrast for observations of weakly backscattering and weakly depolarizing particles. Improved confidence in PSC classification can be achieved by a more comprehensive consideration of the effect of measurement uncertainties. The particle depolarization ratio is the key to a reliable identification of different PSC types. Hence, detailed information on the calibration of the polarization‐sensitive measurement channels should be provided to assess the findings of a study. Presently, most PSC measurements with lidar are performed at 532 nm only. The information from additional polarization‐sensitive measurements in the near infrared could lead to an improved PSC classification. Coincident lidar‐based temperature measurements at PSC level might provide useful information for an assessment of PSC classification.