Polar Stratospheric Clouds Types Research Articles

Atlas of ACE spectra of clouds and aerosols

Clouds and aerosols play a vital role in the Earth's climate. Detecting polar mesospheric clouds, polar stratospheric clouds and aerosols is useful for monitoring climate change and atmospheric chemistry. ACE (Atmospheric Chemistry Experiment) satellite data are used to provide an infrared spectral atlas of polar mesospheric clouds, three types of polar stratospheric clouds (nitric acid trihydrate, sulfuric/nitric acid ternary solutions, and ice), cirrus clouds, stratospheric smoke from fires and sulfate aerosols. Most of the example spectra have been modeled using the appropriate optical constants and the calculated extinction of sunlight by the particles.

Lagrangian simulation of ice particles and resulting dehydration in the polar winter stratosphere.

Polar stratospheric clouds (PSCs) and cold stratospheric aerosols drive heterogeneous chemistry and play a major role in polar ozone depletion. The Chemical Lagrangian Model of the Stratosphere (CLaMS) simulates the nucleation, growth, sedimentation, and evaporation of PSC particles along individual trajectories. Particles consisting of nitric acid trihydrate (NAT), which contain a substantial fraction of the stratospheric nitric acid (HNO3), were the focus of previous modeling work and are known for their potential to denitrify the polar stratosphere. Here, we carried this idea forward and introduced the formation of ice PSCs and related dehydration into the sedimentation module of CLaMS. Both processes change the simulated chemical composition of the lower stratosphere. Due to the Lagrangian transport scheme, NAT and ice particles move freely in three-dimensional space. Heterogeneous NAT and ice nucleation on foreign nuclei as well as homogeneous ice nucleation and NAT nucleation on preexisting ice particles are now implemented into CLaMS and cover major PSC formation pathways.We show results from the Arctic winter 2009/2010 and from the Antarctic winter 2011 to demonstrate the performance of the model over two entire PSC seasons. For both hemispheres, we present CLaMS results in comparison to measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), and the Microwave Limb Sounder (MLS). Observations and simulations are presented on season-long and vortex-wide scales as well as for single PSC events. The simulations reproduce well both the timing and the extent of PSC occurrence inside the entire vortex. Divided into specific PSC classes, CLaMS results show predominantly good agreement with CALIOP and MIPAS observations, even for specific days and single satellite orbits. CLaMS and CALIOP agree that NAT mixtures are the first type of PSC to be present in both winters. NAT PSC areal coverages over the entire season agree satisfactorily. However, cloud-free areas, next to or surrounded by PSCs in the CALIOP data, are often populated with NAT particles in the CLaMS simulations. Looking at the temporal and vortex-averaged evolution of HNO3, CLaMS shows an uptake of HNO3 from the gas into the particle phase which is too large and happens too early in the simulation of the Arctic winter. In turn, the permanent redistribution of HNO3 is smaller in the simulations than in the observations. The Antarctic model run shows too little denitrification at lower altitudes towards the end of the winter compared to the observations. The occurrence of synoptic-scale ice PSCs agrees satisfactorily between observations and simulations for both hemispheres and the simulated vertical redistribution of water vapor (H2O) is in very good agreement with MLS observations. In summary, a conclusive agreement between CLaMS simulations and a variety of independent measurements is presented.

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.

Development of a Polar Stratospheric Cloud Model Within the Community Earth System Model: Assessment of 2010 Antarctic Winter

AbstractTo simulate polar stratospheric clouds (PSCs) during the Antarctic winter of 2010, we have developed a PSC model within the Community Earth System Model framework that includes detailed microphysics of sulfuric aerosols and three types of PSCs: supercooled ternary solution (STS), nitric acid trihydrate (NAT), and ice. Our model includes two major NAT formation mechanisms, both of which are essential to reproduce the PSC and gas phase chemical features in the 2010 Antarctic winter. Homogeneous nucleation of NAT from STS produces NAT particles with sizes near 8 μm, which are important to properly simulate denitrification and the gas phase HNO3 observed by the Microwave Limb Sounder (MLS). Heterogeneous nucleation of NAT on ice particles or ice particles on NAT and subsequent evaporation of the ice produces NAT particles with sizes from submicrometers to a few micrometers. These particles account for the large backscattering ratio from NAT observed by the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite, especially in the midwinter season. Adding temperature fluctuations from gravity waves is important to produce larger number density and higher backscattering ratio from ice and NAT particles. However, our model needs a better representation of waves to improve the backscattering ratio and gas phase HNO3 compared with observations. Our model also includes homogeneous nucleation of ice from STS and heterogeneous nucleation of ice on NAT. The model reproduces the gas phase H2O during the winter within the uncertainty of the MLS observations.

The role of sulfate aerosol in the formation of cloudiness over the sea

We estimate the impact of sulfate aerosols on cloudiness formation over the sea in the middle troposphere and the involvement of these particles in the formation of polar stratospheric clouds (PSCs) in the lower stratosphere. The first of these problems is solved using a combined model of moist convection and the formation of cloudiness and sulfate aerosols in the troposphere and lower stratosphere over the sea, incorporating natural emissions of sulfur-containing compounds. We have found that a significant source of condensation nuclei in the troposphere is the photochemical transformation of biogenic dimethyl sulfide (in addition to NaCl). The results of numerical experiments indicate that the absence of sulfate aerosols hinders the cloudiness formation over the sea in the middle and upper troposphere. The problem of sulfate aerosol involvement in the formation of supercooled ternary solutions (STSs) (PSC Type Ib) in the lower stratosphere is solved using a mathematical model of global transport of multicomponent gas pollutants and aerosols in the atmosphere. Using the combined model, numerical experiments were performed for the winter season in both hemispheres. Sulfate aerosols were found to really participate in the formation of STS particles. Without their participation, the formation of STS particles in the lower stratosphere would be hindered. We present the results of numerical calculations and discuss the distribution of concentrations of gaseous nitric and sulfuric acids, as well as mass concentrations of these components in STS particles.

Modeling the formation of polar stratospheric clouds with allowance for kinetic and heterogeneous processes

A new mathematical model of global transport of multicomponent gaseous admixtures and aerosols in the atmosphere and the formation of polar stratospheric clouds (PSC) in both hemispheres has been constructed. Two types of PSCs are considered: type Ia, nitric acid trihydrate (NAT), and type Ib, supercooled ternary solutions of H2SO4/HNO3/H2O (STS). New equations are used to describe the variation in gas- and condensed-phase components on the basis of their thermodynamic properties. The formation of PSCs is coupled with sulfate aerosols generated in the upper troposphere and lower stratosphere, and with chemical and kinetic transformation processes (photochemistry, nucleation, condensation/evaporation, and coagulation). Using this coupled model, numerical experiments were performed to reproduce the spatial and temporal variability of PSCs in winter in both hemispheres. First, the formation of primary sulfate aerosols in the atmosphere is considered and then these aerosols are incorporated to the PSC model. The results of the numerical experiments are analyzed.

Contribution of liquid, NAT and ice particles to chlorine activation and ozone depletion in Antarctic winter and spring

Abstract. Heterogeneous reactions in the Antarctic stratosphere are the cause of chlorine activation and ozone depletion, but the relative roles of different types of polar stratospheric clouds (PSCs) in chlorine activation is an open question. We use multi-year simulations of the chemistry-climate model ECHAM5/MESSy for Atmospheric Chemistry (EMAC) to investigate the impact that the various types of PSCs have on Antarctic chlorine activation and ozone loss. One standard and three sensitivity EMAC simulations have been performed. In all simulations a Newtonian relaxation technique using the ERA-Interim reanalysis was applied to simulate realistic synoptic conditions. In the three sensitivity simulations, we only changed the heterogeneous chemistry on PSC particles by switching the chemistry on liquid, nitric acid trihydrate (NAT) and ice particles on and off. The results of these simulations show that the significance of heterogeneous reactions on NAT and ice particles for chlorine activation and ozone depletion in Antarctic winter and spring is small in comparison to the significance of heterogeneous reactions on liquid particles. Liquid particles alone are sufficient to activate almost all of the available chlorine, with the exception of the upper PSC regions between 10 and 30 hPa, where temporarily ice particles show a relevant contribution. Shortly after the first PSC occurrence, NAT particles contribute a small fraction to chlorine activation. Heterogeneous chemistry on liquid particles is responsible for more than 90% of the ozone depletion in Antarctic spring in the model simulations. In high southern latitudes, heterogeneous chemistry on ice particles causes only up to 5 DU of additional ozone depletion in the column and heterogeneous chemistry on NAT particles less than 0.5 DU. The simulated HNO3, ClO and O3 results agree closely with observations from the Microwave Limb Sounder (MLS) onboard NASA's Aura satellite.

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.

Quantifying the role of orographic gravity waves on polar stratospheric cloud occurrence in the Antarctic and the Arctic

The proportion of polar stratospheric clouds due to orographic gravity wave (OGW) forcing is quantified during four Antarctic (2007–2010) and four Arctic (2006/2007 to 2009/2010) winter seasons. OGW‒active days are defined as those days above major polar mountain ranges which have wave‒ice polar stratospheric clouds (PSCs), tropospheric wind conditions appropriate for orographic wave generation and propagation, and stratospheric temperatures below the frost point: 37% of Antarctic days and 12% of Arctic days are OGW‒active. Regions downstream of these mountain ranges are defined using a forward‒trajectory model which follows particle movement from ridge lines for 24 h periods. In both hemispheres in these mountain regions, more than 75% of H2O ice PSCs and around 50% of a high number density liquid‒nitric acid trihydrate mixture class (Mix 2‒enh) are attributed to OGW activity, with the balances due to non‒orographic formation. For the whole Arctic (equatorward of 82°), 25% of Mix 2‒enh and 54% of H2O ice PSCs are attributed to OGWs, while for the whole Antarctic, 7% of Mix 2‒enh and 13% of H2O ice PSCs are attributed to OGWs. For all types of PSC, 5% in the whole Antarctic and 12% in the whole Arctic are attributed to OGW forcing. While gravity waves play a role in PSC formation in the Antarctic, overall it is minor compared with other forcing sources. However, in the synoptically warmer Arctic, much larger proportions of PSCs are due to OGW activity.

Simulation of polar stratospheric clouds in the specified dynamics version of the whole atmosphere community climate model

We evaluate the simulation of polar stratospheric clouds (PSCs) in the Specified Dynamics version of the Whole Atmosphere Community Climate Model for the Antarctic winter 2005. In this model, PSCs are assumed to form instantaneously at a prescribed supersaturation, with a prescribed size distribution and number density. We use satellite observations of the Antarctic winter 2005 of nitric acid, water vapor, and PSCs to test and improve this PSC parameterization. Cloud‐Aerosol Lidar with Orthogonal Polarization observations since 2006 show that in both hemispheres, the dominant PSC type throughout the entire polar winter is a mixture of Nitric Acid Trihydrate (NAT) and Supercooled Ternary Solutions droplets, but typical assumptions about PSC formation in the model at a given supersaturation do not produce such a population of particles and lead to earlier removal of HNO3 from the gas phase compared to observations. In our new PSC scheme, the formation of mixed PSCs is forced by only allowing a fraction of total available HNO3 to freeze to NAT and the remaining part to form STS. With this approach, a mixture of both is present throughout the winter, in agreement with observations. This approach yields good agreement with observations in terms of temperature‐dependent removal of gas‐phase HNO3 and irreversible denitrification. In addition to nitric acid containing PSCs, we also investigate ice PSCs. We show that the choice of required saturation ratio of water vapor for ice formation can significantly improve the calculated vertical distribution of water vapor and is required to produce good agreement with observations.

Depolarization ratio of polar stratospheric clouds in coastal Antarctica: comparison analysis between ground-based Micro Pulse Lidar and space-borne CALIOP observations

Abstract. Polar stratospheric clouds (PSCs) play an important role in polar ozone depletion, since they are involved in diverse ozone destruction processes (chlorine activation, denitrification). The degree of that ozone reduction is depending on the type of PSCs, and hence on their occurrence. Therefore PSC characterization, mainly focused on PSC-type discrimination, is widely demanded. The backscattering (R) and volume linear depolarization (δV) ratios are the parameters usually used in lidar measurements for PSC detection and identification. In this work, an improved version of the standard NASA/Micro Pulse Lidar (MPL-4), which includes a built-in depolarization detection module, has been used for PSC observations above the coastal Antarctic Belgrano II station (Argentina, 77.9° S 34.6° W, 256 m a.s.l.) since 2009. Examination of the MPL-4 δV feature as a suitable index for PSC-type discrimination is based on the analysis of the two-channel data, i.e., the parallel (p-) and perpendicular (s-) polarized MPL signals. This study focuses on the comparison of coincident δV-profiles as obtained from ground-based MPL-4 measurements during three Antarctic winters with those reported from the space-borne lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite in the same period (83 simultaneous cases are analysed for 2009–2011 austral winter times). Three different approaches are considered for the comparison analysis between both lidar profile data sets in order to test the degree of agreement: the correlation coefficient (CC), as a measure of the relationship between both PSC vertical structures; the mean differences together with their root mean square (RMS) values found between data sets; and the percentage differences (BIAS), parameter also used in profiling comparisons between CALIOP and other ground-based lidar systems. All of them are examined as a function of the CALIPSO ground-track distance from the Belgrano II station. Results represent a relatively good agreement between both ground-based MPL-4 and space-borne CALIOP profiles of the volume linear depolarization ratio δV for PSC events, once the MPL-4 depolarization calibration parameters are applied. Discrepancies between CALIOP and MPL-4 profiles in vertical layering structure are enhanced from 20 km up, likely due to a decrease of the signal-to-noise ratio (SNR) for both lidar systems at those altitudes. Regarding the results obtained from the mean and the percentage differences found between MPL-4 and CALIOP δV profiles, a predominance of negative values is also observed, indicating a generalized underestimation of the MPL-4 depolarization as compared to that reported by CALIOP. However, absolute differences between those δV-profile data sets are no higher than a 10 ± 11% in average. Moreover, the degree of agreement between both lidar δV data sets is slightly dependent on the CALIPSO ground-track overpass distance from the Belgrano II station. That is, small discrepancies are found when CALIPSO ground-track distance is as close as far from the ground-based station. These results would indicate that MPL-4 depolarization observations would reflect relatively well the PSC field that CALIOP can detect at relatively large distances from the ground-based station. As a consequence, PSC properties can be statistically similar, on average, over large volumes, and hence the present weak disagreement found between both the lidar δV data sets can be likely dominated by small spatial PSC inhomogeneities along the CALIPSO separation from the station. This statement is based on the fact that Belgrano II is a station located well inside the stable Antarctic polar vortex, allowing determined thermodynamic conditions leading to a very low variability in the PSC field, and in their properties.

Fast cloud parameter retrievals of MIPAS/Envisat

Abstract. The infrared limb spectra of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Envisat satellite include detailed information on tropospheric clouds and polar stratospheric clouds (PSC). However, no consolidated cloud product is available for the scientific community. Here we describe a fast prototype processor for cloud parameter retrieval from MIPAS (MIPclouds). Retrieval of parameters such as cloud top height, temperature, and extinction are implemented, as well as retrieval of microphysical parameters, e.g. effective radius and the integrated quantities over the limb path (surface area density and volume density). MIPclouds classifies clouds as either liquid or ice cloud in the upper troposphere and polar stratospheric clouds types in the stratosphere based on statistical combinations of colour ratios and brightness temperature differences. Comparison of limb measurements of clouds with model results or cloud parameters from nadir looking instruments is often difficult due to different observation geometries. We therefore introduce a new concept, the limb-integrated surface area density path (ADP). By means of validation and radiative transfer calculations of realistic 2-D cloud fields as input for a blind test retrieval (BTR), we demonstrate that ADP is an extremely valuable parameter for future comparison with model data of ice water content, when applying limb integration (ray tracing) through the model fields. In addition, ADP is used for a more objective definition of detection thresholds of the applied detection methods. Based on BTR, a detection threshold of ADP = 107 μm2 cm−2 and an ice water content of 10−5 g m−3 is estimated, depending on the horizontal and vertical extent of the cloud. Intensive validation of the cloud detection methods shows that the limb-sounding MIPAS instrument has a sensitivity in detecting stratospheric and tropospheric clouds similar to that of space- and ground-based lidars, with a tendency for higher cloud top heights and consequently higher sensitivity for some of the MIPAS detection methods. For the high cloud amount (HCA, pressure levels below 440 hPa) on global scales the sensitivity of MIPAS is significantly greater than that of passive nadir viewers. This means that the high cloud fraction will be underestimated in the ISCCP dataset compared to the amount of high clouds deduced by MIPAS. Good correspondence in seasonal variability and geographical distribution of cloud occurrence and zonal means of cloud top height is found in a detailed comparison with a climatology for subvisible cirrus clouds from the Stratospheric Aerosol and Gas Experiment II (SAGE II) limb sounder. Overall, validation with various sensors shows the need to consider differences in sensitivity, and especially the viewing geometries and field-of-view size, to make the datasets comparable (e.g. applying integration along the limb path through nadir cloud fields). The simulation of the limb path integration will be an important issue for comparisons with cloud-resolving global circulation or chemical transport models.

On the linkage between tropospheric and Polar Stratospheric clouds in the Arctic as observed by space–borne lidar

Abstract. The type of Polar stratospheric clouds (PSCs) as well as their temporal and spatial extent are important for the occurrence of heterogeneous reactions in the polar stratosphere. The formation of PSCs depends strongly on temperature. However, the mechanisms of the formation of solid PSCs are still poorly understood. Recent satellite studies of Antarctic PSCs have shown that their formation can be associated with deep-tropospheric clouds which have the ability to cool the lower stratosphere radiatively and/or adiabatically. In the present study, lidar measurements aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite were used to investigate whether the formation of Arctic PSCs can be associated with deep-tropospheric clouds as well. Deep-tropospheric cloud systems have a vertical extent of more than 6.5 km with a cloud top height above 7 km altitude. PSCs observed by CALIPSO during the Arctic winter 2007/2008 were classified according to their type (STS, NAT, or ice) and to the kind of underlying tropospheric clouds. Our analysis reveals that 172 out of 211 observed PSCs occurred in connection with tropospheric clouds. 72% of these 172 observed PSCs occurred above deep-tropospheric clouds. We also find that the type of PSC seems to be connected to the characteristics of the underlying tropospheric cloud system. During the Arctic winter 2007/2008 PSCs consisting of ice were mainly observed in connection with deep-tropospheric cloud systems while no ice PSC was detected above cirrus. Furthermore, we find no correlation between the occurrence of PSCs and the top temperature of tropospheric clouds. Thus, our findings suggest that Arctic PSC formation is connected to adiabatice cooling, i.e. dynamic effects rather than radiative cooling.

Investigation of polar stratospheric clouds in January 2008 by means of ground-based and spaceborne lidar measurements and microphysical box model simulations

Polar stratospheric clouds (PSCs) play a key role in heterogeneous chemistry and ozone depletion in the lower stratosphere. The type of PSC as well as their temporal and spatial extent are importan ...

Simulation of polar stratospheric clouds in the chemistry-climate-model EMAC via the submodel PSC

Abstract. The submodel PSC of the ECHAM5/MESSy Atmospheric Chemistry model (EMAC) has been developed to simulate the main types of polar stratospheric clouds (PSC). The parameterisation of the supercooled ternary solutions (STS, type 1b PSC) in the submodel is based on Carslaw et al. (1995b), the thermodynamic approach to simulate ice particles (type 2 PSC) on Marti and Mauersberger (1993). For the formation of nitric acid trihydrate (NAT) particles (type 1a PSC) two different parameterisations exist. The first is based on an instantaneous thermodynamic approach from Hanson and Mauersberger (1988), the second is new implemented and considers the growth of the NAT particles with the aid of a surface growth factor based on Carslaw et al. (2002). It is possible to choose one of this NAT parameterisation in the submodel. This publication explains the background of the submodel PSC and the use of the submodel with the goal of simulating realistic PSC in EMAC.

Can gravity waves significantly impact PSC occurrence in the Antarctic?

Abstract. A combination of POAM III aerosol extinction and CHAMP RO temperature measurements are used to examine the role of atmospheric gravity waves in the formation of Antarctic Polar Stratospheric Clouds (PSCs). POAM III aerosol extinction observations and quality flag information are used to identify Polar Stratospheric Clouds using an unsupervised clustering algorithm. A PSC proxy, derived by thresholding Met Office temperature analyses with the PSC Type Ia formation temperature (TNAT), shows general agreement with the results of the POAM III analysis. However, in June the POAM III observations of PSC are more abundant than expected from temperature threshold crossings in five out of the eight years examined. In addition, September and October PSC identified using temperature thresholding is often significantly higher than that derived from POAM III; this observation probably being due to dehydration and denitrification. Comparison of the Met Office temperature analyses with corresponding CHAMP observations also suggests a small warm bias in the Met Office data in June. However, this bias cannot fully explain the differences observed. Analysis of CHAMP data indicates that temperature perturbations associated with gravity waves may partially explain the enhanced PSC incidence observed in June (relative to the Met Office analyses). For this month, approximately 40% of the temperature threshold crossings observed using CHAMP RO data are associated with small-scale perturbations. Examination of the distribution of temperatures relative to TNAT shows a large proportion of June data to be close to this threshold, potentially enhancing the importance of gravity wave induced temperature perturbations. Inspection of the longitudinal structure of PSC occurrence in June 2005 also shows that regions of enhancement are geographically associated with the Antarctic Peninsula; a known mountain wave "hotspot". The latitudinal variation of POAM III observations means that we only observe this region in June–July, and thus the true pattern of enhanced PSC production may continue operating into later months. The analysis has shown that early in the Antarctic winter stratospheric background temperatures are close to the TNAT threshold (and PSC formation), and are thus sensitive to temperature perturbations associated with mountain wave activity near the Antarctic peninsula (40% of PSC formation). Later in the season, and at latitudes away from the peninsula, temperature perturbations associated with gravity waves contribute to about 15% of the observed PSC (a value which corresponds well to several previous studies). This lower value is likely to be due to colder background temperatures already achieving the TNAT threshold unaided. Additionally, there is a reduction in the magnitude of gravity waves perturbations observed as POAM III samples poleward of the peninsula.

Polar Stratospheric Cloud Observations in the 2006/07 Arctic Winter by Using an Improved Micropulse Lidar

Abstract The potential of a new improved version of micropulse lidar (MPL-4) on polar stratospheric cloud (PSC) detection is evaluated in the Arctic over Ny-Ålesund (79°N, 12°E), Norway. The campaign took place from January to February 2007 in the frame of the International Polar Year (IPY) activities. Collocated Alfred Wegener Institute (AWI) Koldewey Aerosol Raman Lidar (KARL) devoted to long-term Arctic PSC monitoring is used for validation purposes. PSC detection is based on lidar retrievals of both backscattering ratio R and volume depolarization ratio δV. Two episodes were unequivocally attributed to PSCs: 21–22 January and 5–6 February 2007, showing a good correlation between MPL-4 and KARL backscattering ratio datasets (mean correlation coefficient = 0.92 ± 0.03). PSC layered structures were characterized for four observational periods coincident with KARL measurements. Also, PSC type classification was determined depending on the retrieved R and δV values as compared with those obtained by KARL long-term Arctic PSC measurements. Tropospheric cloud cover from lidar observations and both ECMWF potential vorticity and temperature at 475 K, in addition to temperature profiles from AWI daily radiosoundings, are also reported. Height-resolved and temporal evolution of both PSC episodes obtained from MPL-4 measurements clearly show that MPL-4 is a suitable instrument to provide long-term PSC statistic monitoring in polar regions. These results are the first reported on PSC detection in the Arctic by using a low-energy and highly pulsed lidar operating on autonomous and full-time continuous mode MPL-4.

Size distribution time series of a polar stratospheric cloud observed above Arctic Lidar Observatory for Middle Atmosphere Research (ALOMAR) (69°N) and analyzed from multiwavelength lidar measurements during winter 2005

A case study of a polar stratospheric cloud (PSC) is described using multiwavelength (355, 532, and 1064 nm) lidar measurements performed at the Arctic Lidar Observatory for Middle Atmosphere Research (ALOMAR) on 6 December 2005. Rotational Raman signals at 529 and 530 nm are used to derive a temperature field within the cloud using the rotational Raman technique (RRT). The PSC size distributions are retrieved between 1500 and 2000 UTC through a combination of statistical filtering and best match approaches. Several PSC types were detected between 22 and 26 km during the measurement session. Liquid ternary aerosols are identified before about 1600 and after 1900 UTC typically; their averaged retrieved size distribution parameters and associated errors at the backscatter peak are: No ≈ 1–10 cm−3 (50%), rm ≈ 0.15 μm (20%), and σ ≈ 1.2 (15%). A mode of much larger particles is detected between 1600 and 1900 UTC (No ≈ 0.04 cm−3 (30%), rm ≈ 1.50 μm (15%), and σ ≈ 1.37 (10%). The different PSC types are also identified using standard semiempirical classifications, based on lidar backscatter, temperature, and depolarization. Overall, the characteristics of the retrieved size distributions are consistent with these classifications. They all suggest that these very large particles are certainly nitric acid trihydrate that could have been generated by the strong gravity wave activity visible in the temperature profiles. The results demonstrate that multiwavelength lidar data coupled to both RRT temperatures and our size distribution retrieval can provide useful additional information for identification of PSC types and for direct comparisons with microphysical model simulations.

Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

Abstract. A method for estimating the stratospheric particle size distribution from multiwavelength lidar measurements is presented. It is based on matching measured and model-simulated backscatter coefficients. The lidar backscatter coefficients measured at the three commonly used wavelengths 355, 532 and 1064 nm are compared to a precomputed look-up table of model-calculated values. The optical model assumes that particles are spherical and that their size distribution is unimodal. This inverse problem is not trivial because the optical model is highly non-linear with a strong sensitivity to the size distribution parameters in some cases. The errors in the lidar backscatter coefficients are explicitly taken into account in the estimation. The method takes advantage of the statistical properties of the possible solution cluster to identify the most probable size distribution parameters. In order to discard model-simulated outliers resulting from the strong non-linearity of the model, solutions farther than one standard deviation of the median values of the solution cluster are filtered out, because the most probable solution is expected to be in the densest part of the cluster. Within the filtered solution cluster, the estimation algorithm minimizes a cost function of the misfit between measurements and model simulations. Two validation cases are presented on Polar Stratospheric Cloud (PSC) events detected above the ALOMAR observatory (69° N – Norway). A first validation is performed against optical particle counter measurements carried out in January 1996. In non-depolarizing regions of the cloud (i.e. spherical particles), the parameters of an unimodal size distribution and those of the optically dominant mode of a bimodal size distribution are quite successfully retrieved, especially for the median radius and the geometrical standard deviation. As expected, the algorithm performs poorly when solid particles drive the backscatter coefficient. A small bias is identified in modelling the refractive index when compared to previous works that inferred PSC type Ib refractive indices. The accuracy of the size distribution retrieval is improved when the refractive index is set to the value inferred in the reference paper. Our results are then compared to values retrieved with another similar method that does not account for the effect of the measurements errors and the non-linearity of the optical model on the likelihood of the solution. The case considered is a liquid PSC observed over northern Scandinavia on January 2005. An excellent agreement is found between the two methods when our algorithm is applied without any statistical filtering of the solution cluster. However, the solution for the geometrical standard deviation appears to be rather unlikely with a value close to unity (σ≈1.04). When our algorithm is applied with solution filtering, a more realistic value of the standard deviation (σ≈1.27) is found. This highlights the importance of taking into account the non linearity of the model together with the lidar errors, when estimating particle size distribution parameters from lidar measurements.

Spectroscopic evidence for NAT, STS, and ice in MIPAS infrared limb emission measurements of polar stratospheric clouds

Abstract. We have analyzed mid-infrared limb-emission measurements of polar stratospheric clouds (PSCs) by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) during the Antarctic winter 2003 with respect to PSC composition. Coincident Lidar observations from McMurdo were used for comparison with PSC types 1a, 1b and 2. Application of new refractive index data of β-NAT have allowed to accurately simulate the prominent spectral band at 820 cm-1 observed by MIPAS at the location where the Lidar instrument observed type 1a PSCs. Broadband spectral fits covering the range from 780 to 960 cm-1 and from 1220 to 1490 cm-1 showed best agreement with the MIPAS measurements when spectroscopic data of NAT were used to simulate the MIPAS spectra. MIPAS measurements collocated with Lidar observations of Type 1b and Type 2 PSCs could only be reproduced by assuming a composition of supercooled ternary H2SO4/HNO3/H2O solution (STS) and of ice, respectively. Particle radius and number density profiles derived from MIPAS were generally consistent with the Lidar observations. Only in the case of ice clouds, PSC volumes are partly underestimated by MIPAS due to large cloud optical thickness in the limb-direction. A comparison of MIPAS cloud composition and Lidar PSC-type determination based on all available MIPAS-Lidar coincident measurements revealed good agreement between PSC-types 1a, 1b and 2, and NAT, STS and ice, respectively. We could not find spectroscopic evidence for the presence of nitric acid dihydrate (NAD) from MIPAS observations of PSCs over Antarctica in 2003.