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Cloud identification from satellites is considerably challenging in polar environments due to the similar radiative properties of surface and ice clouds, making it difficult to detect and distinguish cloud features. CIC (Cloud Identification and Classification) is a machine learning algorithm adopted as the official software in the ESA Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) (Palchetti et al., 2020) End2End simulator (FE2ES). CIC is based on Principal Component Analysis and performs cloud detection and multi-scene classification. It is adaptable to every type of sensor and is particularly suitable when a small number of elements are available for the Training Set. Assessment studies have already been conducted to evaluate the performances of the algorithm in multiple conditions. In Maestri et al. (2019), CIC was applied to simulated radiance all over the globe, while Magurno et al. (2020) used the algorithm to analyze airborne interferometric spectra. Finally, in Cossich et al. (2021) the algorithm was tested on downwelling radiances collected at Dome-C in Antarctica. In this work, CIC is applied to high spectrally resolved data taken from ground and, for the first time, from satellites. Ground-based data are collected by the REFIR-PAD sensor (Di Natale et al., 2020), covering the far and mid-infrared part of the spectrum. Collocated satellite data are measured by IASI (Infrared Atmospheric Sounding Interferometer) which collects upwelling radiance between 3.4 and 15.5 μm. The period under study spans from 2012 to 2022. CIC results applied to ground-measured spectra are compared to IASI’s L2 classification products. Large discrepancies between the two classifications are observed, indicating an overestimation of the cloud occurrence in case of IASI. A verification is obtained using collocated ground-based LIDAR measurements, which are available for subsets of the collocated radiances. Finally, the CIC algorithm is trained with a subset of IASI data collocated with REFIR-PAD and LIDAR measurements. The training set is defined also with the help of the Advanced Very High Resolution Radiometer (AVHRR) on board of MetOp satellites. The AVHRR has 1 km resolution (at the nadir) and its collocated measurements are used to evaluate the scene homogeneity in the satellite field of view. Statistical analyses are then performed on IASI spectra using the CIC classification. Results indicate a much better agreement with ground-based data, improving the cloud occurrence provided in IASI L2 products.

Statistics on the occurrence of clear skies, ice clouds, and mixed-phase clouds over Concordia Station, in the Antarctic Plateau, are provided for multiple timescales and analyzed in relation to simultaneous meteorological parameters measured at the surface. Results are obtained by applying a machine learning cloud identification and classification (CIC) code to 4 years of measurements between 2012–2015 of downwelling high-spectral-resolution radiances, measured by the Radiation Explorer in the Far Infrared – Prototype for Applications and Development (REFIR-PAD) spectroradiometer. The CIC algorithm is optimized for Antarctic sky conditions and results in a total hit rate of almost 0.98, where 1.0 is a perfect score, for the identification of the clear-sky, ice cloud, and mixed-phase cloud classes. Scene truth is provided by lidar measurements that are concurrent with REFIR-PAD. The CIC approach demonstrates the key role of far-infrared spectral measurements for clear–cloud discrimination and for cloud phase classification. Mean annual occurrences are 72.3 %, 24.9 %, and 2.7 % for clear sky, ice clouds, and mixed-phase clouds, respectively, with an inter-annual variability of a few percent. The seasonal occurrence of clear sky shows a minimum in winter (66.8 %) and maxima (75 %–76 %) during intermediate seasons. In winter the mean surface temperature is about 9 ∘C colder in clear conditions than when ice clouds are present. Mixed-phase clouds are observed only in the warm season; in summer they amount to more than one-third of total observed clouds. Their occurrence is correlated with warmer surface temperatures. In the austral summer, the mean surface air temperature is about 5 ∘C warmer when clouds are present than in clear-sky conditions. This difference is larger during the night than in daylight hours, likely due to increased solar warming. Monthly mean results are compared to cloud occurrence and fraction derived from gridded (Level 3) satellite products from both passive and active sensors. The differences observed among the considered products and the CIC results are analyzed in terms of footprint sizes and sensors' sensitivities to cloud optical and geometrical features. The comparison highlights the ability of the CIC–REFIR-PAD synergy to identify multiple cloud conditions and study their variability at different timescales.

As the near-surface atmosphere over the Antarctic Plateau is cold and pristine, its physico-chemical conditions resemble to a certain extent those of the high troposphere where cirrus clouds form. In this paper, we carry out an observational analysis of two shallow fog clouds forming in situ at cirrus temperatures – that is, temperatures lower than 235 K – at Dome C, inner Antarctic Plateau. The combination of lidar profiles with temperature and humidity measurements from advanced thermo-hygrometers along a 45 m mast makes it possible to characterise the formation and development of the fog. High supersaturations with respect to ice are observed before the initiation of fog, and the values attained suggest that the nucleation process at play is the homogeneous freezing of solution aerosol droplets. This is the first time that in situ observations show that this nucleation pathway can be at the origin of an ice fog. Once nucleation occurs, the relative humidity gradually decreases down to subsaturated values with respect to ice in a few hours, owing to vapour deposition onto ice crystals and turbulent mixing. The development of fog is tightly coupled with the dynamics of the boundary layer which, in the first study case, experiences a weak diurnal cycle, while in the second case, it transits from a very stable to a weakly stable dynamical regime. Overall, this paper highlights the potential of the site of Dome C for carrying out observational studies of very cold cloud microphysical processes in natural conditions and using in situ ground-based instruments.

Selected case studies of precipitating ice clouds at Dome-C (Antarctic Plateau) are used to test a new approach for the estimation of ice cloud reflectivity at 24 GHz (12.37 mm of wavelength) using ground-based far infrared spectral measurements from the REFIR-PAD Fourier transform spectroradiometer and backscattering/depolarization lidar profiles. The resulting reflectivity is evaluated with the direct reflectivity measurements provided by a co-located micro rain radar (MRR) operating at 24 GHz, which is able to detect falling crystals with large particle size, typically above 500 μm. To obtain the 24 GHz reflectivity, we used the particle effective diameter and the cloud optical depth retrieved from the far infrared spectral radiances provided by REFIR-PAD and the tropospheric co-located backscattering lidar to calculate the modal radius and the intercept of the particle size distribution. From these, the theoretical reflectivity at 24 GHz is obtained by integrating the size distribution over different microwave cross sections for various habit crystals provided by Eriksson et al. (2018) databases. From the comparison with the radar reflectivity measurements, we found that the column-like habits and the plates/columnar crystal aggregates show the best agreement with the MRR observations. The presence of (hexagonal) columns is confirmed both by the presence of 22° solar halos, detected by the HALO-CAMERA, and by the crystal images taken by the ICE-CAMERA, operating in proximity of REFIR-PAD and the MRR. The average crystal lengths obtained from the retrieved size distribution are also compared to the ones estimated from the ICE-CAMERA images. The agreement between the two results confirms that the retrieved parameters of the particle size distributions correctly reproduce the observations.

Clouds affect the Earth climate with an impact that depends on the cloud nature (solid/ liquid water). Although the Antarctic climate is changing rapidly, cloud observations are sparse over Antarctica due to few ground stations and satellite observations. The Concordia station is located on the East Antarctic Plateau (75° S, 123° E, 3233 m above mean sea level), one of the driest and coldest places on Earth. We used observations of clouds, temperature, liquid water and surface radiation performed at Concordia during 4 austral summers (December 2018–2021) to analyze the link between liquid water and temperature and its impact on surface radiation in the presence of supercooled liquid water (liquid water for temperature less than 0 °C) clouds (SLWCs). Our analysis shows that, within SLWCs, temperature logarithmically increases from -36.0 °C to -16.0 °C when liquid water path increases from 1.0 to 14.0 g m-2, and SLWCs positively impact the net surface radiation, which logarithmically increases by 0.0 to 50.0 W m-2 when liquid water path increases from 1.7 to 3.0 g m-2. We finally estimate that SLWCs have a great potential radiative impact over Antarctica whatever the season considered, up to 5.0 W m-2 over the Eastern Antarctic Plateau and up to 30 W m-2 over the Antarctic Peninsula in summer.

Downwelling radiance spectra in the 100-1500 cm-1 interval, measured by the Radiation Explorer in the Far Infrared-Prototype for Applications and Development (REFIR-PAD) spectroradiometer on the Antarctic plateau since 2012, are ingested by an automatic machine learning algorithm, named cloud identification and classification (CIC), to detect and classify the Antarctic clouds. The CIC algorithm is a modified version of the one chained in the End-2-End Simulator (EES) of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission, the next ESA 9th Earth Explorer. CIC sits at the center of the decision tree of the FORUM EES for retrieving clear-sky atmospheric products or cloud properties. Co-located lidar measurements are exploited to define training sets composed of radiance spectra in presence of clear sky, ice clouds or mixed-phase clouds. The CIC is initially tested on a controlled verification subset for optimization. It is demonstrated that the information content in the far infrared (FIR) part of the spectrum is critical for the improvement of the performances of the algorithm to identify thin clouds and for cloud phase classification. A test set of 1726 spectra is then used to estimate the classification error. Unprecedented cloud occurrence statistics concerning more than 4 years of data are provided for multiple time scales and related to meteorological parameters such as surface air temperature and wind direction. The results indicate a clear sky mean annual occurrence of 72.3%, while ice and mixed-phase clouds are observed in 24.9% and 2.7% respectively, with an inter-annual variability of a few percent. The seasonal occurrence of clear sky shows a minimum in winter (66.8%) and maxima (75-76%) during intermediate seasons. In austral winter the mean surface temperature is about 9°C colder in clear conditions than when ice clouds are present. Mixed-phase clouds are observed only in the warm season (November-March). In austral summer they amount to more than one third of total observed clouds. Their occurrence is correlated with warmer surface temperatures. In the summer, the mean surface air temperature is about 5°C warmer when clouds are present than in clear sky conditions. A comparison of the CIC classification with available satellite Level-2 (L2) and Level-3 (L3) products, is provided. Passive (Infrared Atmospheric Sounding Interferometer - IASI, and Moderate Resolution Imaging Spectroradiometer - MODIS), and active (Cloud-Aerosol LiDAR with Orthogonal Polarization - CALIOP, and the Cloud Profiling Radar - CPR) sensors are considered. For selected case studies, a direct comparison between co-located L2 satellite products and parameters retrieved from ground-based observations (REFIR-PAD, lidar) is performed. In case of cloudy scenes, retrieved cloud parameter are used to simulate FORUM like observations and to evaluate the impact of the additional FIR part of spectrum in satellite cloud retrievals from infrared passive measurements. For L3 satellite products, the monthly gridded data are used for comparison. The differences observed among the considered products and the CIC results are analysed in terms of footprint sizes and sensors' sensitivities. The comparison highlights the ability of the CIC/REFIR-PAD to identify multiple cloud conditions from high spectral resolution radiances.

We present preliminary results from the project OPTAIR, aimed to study the optical properties of airborne particles at Concordia Station, on the East Antarctic plateau, and to assess the relationship among the optical properties of particles suspended in air and deposited by the snow. Light scattering data from single particles are collected continuously by a permanent device installed in November 2018, operating the novel Single Particle Extinction and Scattering method and some traditional scattering measurements. Data are put in correlation with LIDAR measurements, with the aim to assess the impact on past and present climate. Results from the Antarctic season 2019 will be presented, showing clear evidence of remarkable changes in the amount of particles, size and optical properties across the year. In particular, about one third of the total cumulative dust particles accumulated in one year is advected during fast dust-rich air mass subsidence events lasting a few hours. This feature is of major importance to glaciological studies based on integrated, multi-annual snow and ice samples.

Studying precipitation at very high latitudes is difficult because of the harsh environmental conditions that limit the external activity of humans and instruments, especially in the polar winter. The direct monitoring of ice crystal habits and size distribution in Antarctic precipitation is important for the validation of the algorithms used for retrieving precipitation from ground-based and satellite-borne radar instruments and for the improvement of the climatological modelling of polar areas. This paper describes an automated device (ICE-CAMERA) specifically developed for the imaging, measurement, and classification of ice precipitation on the Antarctic high plateau. The instrument gives detailed information on precipitation on an hourly basis. The article provides a description of the device and its image processing software. Starting in 2014, the instrument has operated almost unattended all year round at Concordia station, Antarctica (75∘ S, 123∘ E, 3220 m altitude).

A comprehensive analysis of the water budget over the Dome C (Concordia, Antarctica) station has been performed during the austral summer 2018–2019 as part of the Year of Polar Prediction (YOPP) international campaign. Thin (∼100 m deep) supercooled liquid water (SLW) clouds have been detected and analysed using remotely sensed observations at the station (tropospheric depolarization lidar, the H2O Antarctica Microwave Stratospheric and Tropospheric Radiometer (HAMSTRAD), net surface radiation from the Baseline Surface Radiation Network (BSRN)), radiosondes, and satellite observations (CALIOP, Cloud-Aerosol LIdar with Orthogonal Polarization/CALIPSO, Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations) combined with a specific configuration of the numerical weather prediction model: ARPEGE-SH (Action de Recherche Petite Echelle Grande Echelle – Southern Hemisphere). The analysis shows that SLW clouds were present from November to March, with the greatest frequency occurring in December and January when ∼50 % of the days in summer time exhibited SLW clouds for at least 1 h. Two case studies are used to illustrate this phenomenon. On 24 December 2018, the atmospheric planetary boundary layer (PBL) evolved following a typical diurnal variation, which is to say with a warm and dry mixing layer at local noon thicker than the cold and dry stable layer at local midnight. Our study showed that the SLW clouds were observed at Dome C within the entrainment and the capping inversion zones at the top of the PBL. ARPEGE-SH was not able to correctly estimate the ratio between liquid and solid water inside the clouds with the liquid water path (LWP) strongly underestimated by a factor of 1000 compared to observations. The lack of simulated SLW in the model impacted the net surface radiation that was 20–30 W m−2 higher in the BSRN observations than in the ARPEGE-SH calculations, mainly attributable to the BSRN longwave downward surface radiation being 50 W m−2 greater than that of ARPEGE-SH. The second case study took place on 20 December 2018, when a warm and wet episode impacted the PBL with no clear diurnal cycle of the PBL top. SLW cloud appearance within the entrainment and capping inversion zones coincided with the warm and wet event. The amount of liquid water measured by HAMSTRAD was ∼20 times greater in this perturbed PBL than in the typical PBL. Since ARPEGE-SH was not able to accurately reproduce these SLW clouds, the discrepancy between the observed and calculated net surface radiation was even greater than in the typical PBL case, reaching +50 W m−2, mainly attributable to the downwelling longwave surface radiation from BSRN being 100 W m−2 greater than that of ARPEGE-SH. The model was then run with a new partition function favouring liquid water for temperatures below −20 down to −40 ∘C. In this test mode, ARPEGE-SH has been able to generate SLW clouds with modelled LWP and net surface radiation consistent with observations during the typical case, whereas, during the perturbed case, the modelled LWP was 10 times less than the observations and the modelled net surface radiation remained lower than the observations by ∼50 W m−2. Accurately modelling the presence of SLW clouds appears crucial to correctly simulate the surface energy budget over the Antarctic Plateau.

Statistics on the occurrence of clear skies, ice and mixed-phase clouds over the Concordia station, in the Antarctic Plateau, are provided for multiple time scales and analysed in relation to simultaneous meteorological parameters measured at the surface. Results are obtained by applying a machine learning cloud identification and classification code (named CIC) to 4 years of measurements between 2012–2105 of down-welling high spectral resolution radiances, measured by the Radiation Explorer in the Far Infrared-Prototype for Applications and Development (REFIR-PAD) spectroradiometer. The CIC algorithm is optimized for Antarctic sky conditions (clear sky, ice clouds, and mixed-phase clouds) and results in a total hit rate of almost 0.98, where 1.0 is a perfect score. Scene truth is provided by LiDAR measurements that are concurrent with REFIR-PAD. The CIC approach demonstrates the key role of far infrared spectral measurements for clear/cloud discrimination and for cloud phase classification. Mean annual occurrences are 72.3 %, 24.9 % and 2.7 % for clear sky, ice and mixed-phase clouds respectively, with an inter-annual variability of a few percent. The seasonal occurrence of clear sky shows a minimum in winter (66.8 %) and maxima (75–76 %) during intermediate seasons. In winter the mean surface temperature is about 9 °C colder in clear conditions than when ice clouds are present. Mixed-phase clouds are observed only in the warm season; in summer they amount to more than one third of total observed clouds. Their occurrence is correlated with warmer surface temperatures. In the austral summer, the mean surface air temperature is about 5 °C warmer when clouds are present than in clear sky conditions. This difference is larger during the night than in daylight hours, likely due to increased solar warming. A comparison of monthly mean results with cloud occurrence/fraction derived from gridded (Level-3) satellite products, from both passive and active sensors, emphasizes the difficulty of adequately inferring cloud/clear-sky properties in the Antarctic region and highlights the ability of the CIC/REFIR-PAD synergy to identify multiple cloud conditions and study their variability at different time scales.

Optical and microphysical cloud properties are retrieved from measurements acquired in 2013 and 2014 at the Concordia base station in the Antarctic Plateau. Two sensors are used synergistically: a Fourier transform spectroradiometer named REFIR-PAD (Radiation Explorer in Far Infrared-Prototype for Applications and Developments) and a backscattering-depolarization LiDAR. First, in order to identify the cloudy scenes and assess the cloud thermodynamic phase, the REFIR-PAD spectral radiances are ingested by a machine learning algorithm called Cloud Identification and Classification (CIC). For each of the identified cloudy scenes, the nearest (in time) LiDAR backscattering profile is processed by the Polar Threshold (PT) algorithm that allows derivation of the cloud top and bottom heights. Subsequently, using the CIC and PT results as external constraints, the Simultaneous Atmospheric and Clouds Retrieval (SACR) code is applied to the REFIR-PAD spectral radiances. SACR simultaneously retrieves cloud optical depth and effective dimensions and atmospheric vertical profiles of water vapor and temperature. The analysis determines an average effective diameter of 28 μm with an optical depth of 0.76 for the ice clouds. Water clouds are only detected during the austral Summer, and the retrieved properties provide an average droplet diameter of 9 μm and average optical depth equal to four. The estimated retrieval error is about 1% for the ice crystal/droplet size and 2% for the cloud optical depth. The sensitivity of the retrieved parameters to the assumed crystal shape is also assessed. New parametrizations of the optical depth and the longwave downwelling forcing for Antarctic ice and water clouds, as a function of the ice/liquid water path, are presented. The longwave downwelling flux, computed from the top of the atmosphere to the surface, ranges between 70 and 220 W/m2. The estimated cloud longwave forcing at the surface is (31 ± 7) W/m2 and (29 ± 6) W/m2 for ice clouds and (64 ± 12) and (62 ± 11) W/m2 for water clouds, in 2013 and 2014, respectively. The total average cloud forcing for the two years investigated is (46 ± 9) W/m2.

This work aims at determining the best performing mid and far-infrared (MIR and FIR) joint spectral interval to identify and classify clouds in the Antarctic region by mean of a machine learning algorithm.About 1700 spectral-resolved radiances, collected during 2013 by the ground based Radiation Explorer in the Far InfraRed-Prototype for Applications and Development, REFIR-PAD (Palchetti et al., 2015) at Dome C, Antarctic Plateau, are selected in coincidence with the co-located with backscatter and depolarization profiles derived from a tropospheric lidar system (Ricaud et al., 2017) to pre-classify clear sky, ice clouds, or mixed phase clouds.A machine learning cloud identification and classification algorithm named CIC (Maestri et al., 2019), trained with a pre-selected set of REFIR-PAD spectra, is applied to this dataset by assuming that no other information than the spectrum itself is known.The CIC algorithm is applied by considering different spectral intervals, in order to maximize the classification results for each class (clear sky, ice clouds, mixed phase clouds). A CIC "threat score" is defined as the classification true positives divided by the sum of true positives, false positives, and false negatives. The maximization of the threat score is used to assess the algorithm performances that span from 58% to 96% in accordance with the selected interval. The best performing spectral range is the 380-1000 cm-1. The result, besides suggesting the importance of a proper algorithm calibration in accordance with the used sensor, highlights the fundamental role of the FIR part of the spectrum.The calibrated CIC algorithm is then applied to a larger REFIR-PAD dataset of about 90000 spectra collected from 2012 to 2015. Some results of the full dataset cloud classification are also presented.The present work contributes to the preparatory studies for the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission that has recently been selected as ESA’s 9th Earth Explorer mission, scheduled for launch in 2026. References:Maestri, T., Cossich, W., and Sbrolli, I., 2019: Cloud identification and classification from high spectral resolution data in the far infrared and mid-infrared, Atmos. Meas. Tech., 12, pp. 3521 - 3540Palchetti, L., Bianchini, G., Di Natale, G., and Del Guasta, M., 2015: Far infrared radiative properties of water vapor and clouds in Antarctica. Bull. Amer. Meteor. Soc., 96, 1505–1518, doi: http://dx.doi.org/10.1175/BAMS-D-13-00286.1.Ricaud, P., Bazile, E., del Guasta, M., Lanconelli, C., Grigioni, P., and Mahjoub, A., 2017: Genesis of diamond dust, ice fog and thick cloud episodes observed and modelled above Dome C, Antarctica, Atmos. Chem. Phys., 17, 5221–5237, https://doi.org/10.5194/acp-17-5221-2017.

The atmospheric processes determining the isotopic composition of precipitation on the Antarctic plateau are yet to be fully understood, as well as the post-depositional processes altering the snow pristine isotopic signal. Improving the comprehension of these physical mechanisms is of crucial importance for interpreting the isotopic records from ice cores drilled in the low accumulation area of Antarctica, e.g., the upcoming Beyond EPICA drilling at Little Dome C.Up to now, few records of the isotopic composition of precipitation in Antarctica are available, most of them limited in time or sampling frequency. Here we present a 9-year long δ18O and δD record (2008-2016) of precipitation at Concordia base, East Antarctica. The snow is collected daily on a raised platform (1 m), positioned in the clean area of the station; the precipitation collection is still being carried out each year by the winter over personnel.A significant positive correlation between isotopes in precipitation and 2-m air temperature is observed at both seasonal and interannual scale; the lowest temperature and isotopic values are usually recorded during winters characterized by a strongly positive Southern Annular Mode index.To improve the understanding of the mechanisms governing the isotopic composition of precipitation, we compare the isotopic data of Concordia samples with on-site observations, meteorological data from the Dome C AWS of the University of Wisconsin-Madison, as well as with high-resolution simulation results from the isotope-enabled atmospheric general circulation models ECHAM5-wiso and ECHAM6-wiso, nudged with the ERA-Interim and ERA5 reanalyses respectively.

An air ion spectrometer (AIS) was deployed for the first time at the Concordia station at Dome C (75°06′ S, 123°23′ E; 3220 m a. s. l. ), Antarctica during the period 22 December 2010–16 November 2011 for measuring the number size distribution of air ions. In this work, we present results obtained from this air ion data set together with aerosol particle and meteorological data. The main processes that modify the number size distribution of air ions during the measurement period at this high-altitude site included new particle formation (NPF, observed on 85 days), wind-induced ion formation (observed on 36 days), and ion production and loss associated with cloud/fog formation (observed on 2 days). For the subset of days when none of these processes seemed to operate, the concentrations of cluster ions (0.9–1.9 nm) exhibited a clear seasonality, with high concentrations in the warm months and low concentrations in the cold. Compared to event-free days, days with NPF were observed with higher cluster ion concentrations. A number of NPF events were observed with restricted growth below 10 nm, which were termed as suppressed NPF. There was another distinct feature, namely a simultaneous presence of two or three separate NPF and subsequent growth events, which were named as multi-mode NPF events. Growth rates (GRs) were determined using two methods: the appearance time method and the mode fitting method. The former method seemed to have advantages in characterizing NPF events with a fast GR, whereas the latter method is more suitable when the GR was slow. The formation rate of 2 nm positive ions (J2+) was calculated for all the NPF events for which a GR in the 2–3 nm size range could be determined. On average, J2+ was about 0.014 cm−3 s−1. The ion production in relation to cloud/fog formation in the size range of 8–42 nm seemed to be a unique feature at Dome C, which has not been reported elsewhere. These ions may, however, either be multiply charged particles but detected as singly charged in the AIS, or be produced inside the instrument, due to the breakage of cloud condensation nuclei (CCN), possibly related to the instrumental behaviour under the extremely cold condition. For the wind-induced ion formation, our observations suggest that the ions originated more likely from atmospheric nucleation of vapours released from the snow than from mechanical charging of shattered snow flakes and ice crystals.

The possibility separating the contributions of the atmospheric state and ice clouds by using spectral infrared measurements is a fundamental step to quantifying the cloud effect in climate models. A simultaneous retrieval of cloud and atmospheric parameters from infrared wideband spectra will allow the disentanglement of the spectral interference between these variables. In this paper, we describe the development of a code for the simultaneous retrieval of atmospheric state and ice cloud parameters, and its application to the analysis of the spectral measurements acquired by the Radiation Explorer in the Far Infrared – Prototype for Applications and Development (REFIR-PAD) spectroradiometer, which has been in operation at Concordia Station on the Antarctic Plateau since 2012. The code performs the retrieval with a computational time that is comparable with the instrument acquisition time. Water vapour and temperature profiles and the cloud optical and microphysical properties, such as the generalised effective diameter and the ice water path, are retrieved by exploiting the 230–980 cm−1 spectral band. To simulate atmospheric radiative transfer, the Line-By-Line Radiative Transfer Model (LBLRTM) has been integrated with a specifically developed subroutine based on the δ-Eddington two-stream approximation, whereas the single-scattering properties of cirrus clouds have been derived from a database for hexagonal column habits. In order to detect ice clouds, a backscattering and depolarisation lidar, co-located with REFIR-PAD has been used, allowing us to infer the position and the cloud thickness to be used in the retrieval. A climatology of the vertical profiles of water vapour and temperature has been performed by using the daily radiosounding available at the station at 12:00 UTC. The climatology has been used to build an a priori profile correlation to constrain the fitting procedure. An optimal estimation method with the Levenberg–Marquardt approach has been used to perform the retrieval. In most cases, the retrieved humidity and temperature profiles show a good agreement with the radiosoundings, demonstrating that the simultaneous retrieval of the atmospheric state is not biased by the presence of cirrus clouds. Finally, the retrieved cloud parameters allow us to study the relationships between cloud temperature and optical depth and between effective particle diameter and ice water content. These relationships are similar to the statistical correlations measured on the Antarctic coast at Dumont d'Urville and in the Arctic region.

A comprehensive analysis of the water budget over the Dome C (Concordia, Antarctica) station has been performed during the austral summer 20182019 as part of the Year of Polar Prediction (YOPP) international campaign. Thin (~100-m) supercooled liquid water (SLW) clouds have been detected and analysed using remotely sensed observations at the station (tropospheric depolarization LIDAR, microwave radiometer HAMSTRAD, net surface radiation from Baseline Surface Radiation Network, BSRN), radiosondes and using satellite observations (CALIOP/CALIPSO) combined with a specific configuration of the Numerical Weather Prediction model: ARPEGE-SH. Two case studies are used to illustrate this phenomenon. On 24 December 2018, the atmospheric planetary boundary layer (PBL) evolved following a typical diurnal variation, that is to say with a warm and dry mixing layer at local noon thicker than the cold and dry stable layer at local midnight. Our study showed that the SLW clouds were observed at Dome C within the entrainment and the capping inversion zones at the top of the PBL. ARPEGE-SH was not able to correctly estimate the ratio between liquid and solid water inside the clouds. The SLW content was always strongly underestimated in the studied cases. The lack of simulated SLW in the model impacted the net surface radiation that was 2030Wm2 higher in the BSRN observations than in the ARPEGE-SH calculations, mainly attributable to longwave downward surface radiation from BSRN being 50Wm2 greater than that of ARPEGE-SH. On 20 December 2018, a warm and wet episode impacted the PBL with no clear diurnal cycle of the PBL top height. SLW cloud appearance coincided with the warm and wet event within the entrainment and capping inversion zones. The amount of liquid water measured by HAMSTRAD was ~20 times greater in this perturbed PBL than in the typical PBL. Since ARPEGE-SH was not able to accurately reproduce these SLW clouds, the discrepancy between the observed and calculated net surface radiation was even greater than in the typical PBL period, reaching +50Wm2, mainly attributable to longwave downward surface radiation from BSRN being 100Wm2 greater than that of ARPEGE-SH. The absence of SLW clouds in NWPs over Antarctica may indicate an incorrect simulation of the radiative budget of the polar atmosphere.

One year (2013) of high spectral resolution measurements of downwelling radiance in the 100-1,400 cm(-1) range, taken by the Fourier Transform Spectrometer REFIR-PAD at the research station Concordia (Antarctic Plateau), is analyzed. Optically thin ice clouds are identified by means of a new identification/classification tool based on a Support Vector Machine algorithm. The use of transparent microwindow channels in the Far InfraRed (FIR) spectral region (100-667 cm(-1)) is shown to be of great importance in the identification and classification of cloud type. In particular, the channels between 380 and 575 cm(-1) are key channels for the clear/cloud and phase identification due to their sensitivity to cloud properties; in addition, FIR channels down to 238 cm(-1) are exploited for the selection of precipitating or nonprecipitating cases because of their sensitivity also to water vapor content. A subset of 26 cases of nonprecipitating ice clouds is selected based on the presence of colocated LIDAR and radiosonde data. REFIR-PAD channel in the 800-1,000 cm(-1) are used to derived optical and microphysical properties for four different assumptions concerning the crystal habits. Results, showing a correlation between cloud base temperature, optical depth, and particle size distribution effective dimensions, are compared with what found in literature. Based on the retrievals, forward simulations are also run over the whole sensor spectral interval, and results are compared to data. The simulation-data residuals in the FIR are evaluated for selected "window" channels and analyzed in relation to crystal's habit assumption, cloud retrieved features, and atmospheric water vapor content.

The Antarctic Plateau snowpack is an important environment for the mercury geochemical cycle. We have extensively characterized and compared the changes in surface snow and atmospheric mercury concentrations that occur at Dome C. Three summer sampling campaigns were conducted between 2013 and 2016. The three campaigns had different meteorological conditions that significantly affected mercury deposition processes and its abundance in surface snow. In the absence of snow deposition events, the surface mercury concentration remained stable with narrow oscillations, while an increase in precipitation results in a higher mercury variability. The Hg concentrations detected confirm that snowfall can act as a mercury atmospheric scavenger. A high temporal resolution sampling experiment showed that surface concentration changes are connected with the diurnal solar radiation cycle. Mercury in surface snow is highly dynamic and it could decrease by up to 90% within 4/6 h. A negative relationship between surface snow mercury and atmospheric concentrations has been detected suggesting a mutual dynamic exchange between these two environments. Mercury concentrations were also compared with the Br concentrations in surface and deeper snow, results suggest that Br could have an active role in Hg deposition, particularly when air masses are from coastal areas. This research presents new information on the presence of Hg in surface and deeper snow layers, improving our understanding of atmospheric Hg deposition to the snow surface and the possible role of re-emission on the atmospheric Hg concentration. © 2018 Elsevier Ltd

Water vapor and clouds are among the most important greenhouse components whose radiative features cover all the broad spectral range of the thermal emission of the atmosphere. Typically more than 40% of the total thermal emission of Earth occurs in the far-infrared (FIR) spectral region from 100 to 667 cm−1 (wavelengths from 100 to 15 µm). Nevertheless, this spectral region has not ever been fully covered down to 100 cm−1 by space missions, and only a few ground-based experiments exist because of the difficulty of performing measurements from high altitude and very dry locations where the atmosphere is sufficiently transparent to observe the FIR emission features. To cover this lack of observations, the Italian experiment “Radiative Properties of Water Vapor and Clouds in Antarctica” has collected a 2-yr dataset of spectral measurements of the radiance emitted by the atmosphere and by clouds, such as cirrus and polar stratospheric clouds, from 100 to 1,400 cm−1 (100–7 µm of wavelength), including the underexplored FIR region, along with polarization-sensitive lidar observations, daily radiosondes, and other ancillary information to characterize the atmosphere above the site. Measurements have been performed almost continuously with a duty cycle of 6 out of 9 h, from the Italian–French base of Concordia at Dome C over the Antarctic Plateau at 3,230 m MSL, in all-sky conditions since 2012. Because of the uniqueness of the observations, this dataset will be extremely valuable for evaluating the accuracy of atmospheric absorption models (both gas and clouds) in the underexplored FIR and to detect possible daily, seasonal, and annual climate signatures.

New calculations of the relative optical air mass function are made over the 0°–87° range of apparent solar zenith angle θ, for various vertical profiles of background aerosol, diamond dust and thin cirrus cloud particle extinction coefficient in the Arctic and Antarctic atmospheres. The calculations were carried out by following the Tomasi and Petkov (2014) procedure, in which the above-mentioned vertical profiles derived from lidar observations were used as weighting functions. Different sets of lidar measurements were examined, recorded using: (i) the Koldewey-Aerosol-Raman Lidar (KARL) system (AWI, Germany) at Ny-Ålesund (Spitsbergen, Svalbard) in January, April, July and October 2013, (ii) the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite-based sensor over Barrow (Alaska), Eureka (Nunavut, Canada) and Sodankylä (northern Finland), and Neumayer III, Mario Zucchelli and Mirny coastal stations in Antarctica in the local summer months of the last two years, (iii) the National Institute of Optics (INO), National Council of Research (CNR) Antarctic lidar at Dome C on the Antarctic Plateau for a typical “diamond dust” case, and (iv) the KARL lidar at Ny-Ålesund and the University of Rome/National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) lidar at Thule (northwestern Greenland) for some cirrus cloud layers in the middle and upper troposphere. The relative optical air mass calculations are compared with those obtained by Tomasi and Petkov (2014) to define the seasonal changes produced by aerosol particles, diamond dust and cirrus clouds. The results indicate that the corresponding air mass functions generally decrease as angle θ increases with rates that are proportional to the increase in the pure aerosol, diamond dust and cirrus cloud particle optical thickness.

The first results of a campaign of intensive observation of precipitation in Dumont d'Urville, Antarctica, are presented. Several instruments collected data from October 2015, including a polarimetric weather radar (MXPol), a Micro Rain Radar (MRR), a weighing gauge (Pluvio2), and a Multi-Angle Snowflake Camera (MASC). These instruments collected the first model-free measurements of precipitation in the region in the region of Terre Adélie (Adélie Land), including of precipitation microphysics. Microphysical observations during the austral summer 2015/2016 showed that, close to ground level, aggregates are the dominant hydrometeor type, together with small ice particles (mostly originating from blowing snow), and that riming often occurs. Contamination of the Pluvio2 measurements in windy conditions is observed and partly removed through synergistic use of MRR data. The yearly accumulated precipitation of snow (300 m above ground), obtained by means of a local conversion relation of MRR data, trained on the Pluvio2 measurement of the summer period, is estimated to be 815 mm of water equivalent, with a confidence interval ranging between 739.5 to 989 mm. Climatological data obtained from satellite-borne radars, and the ERA-Interim reanalysis of the European Center for Medium-Range Weather Forecasts (ECMWF) both provide lower yearly totals: 655 mm for ERA-Interim, while 679 mm for the climatological data over DDU. ERA-Interim seems to overestimate the occurrence of low-intensity precipitation events especially in summer, while visual observations conducted at the research stations all year long seem to underestimate it. Overall, this manuscript provides insightful examples of the added values of precipitation monitoring in Antarctica with a synergistic use of in-situ and remote sensing measurements.

Episodes of thick cloud and diamond dust/ice fog were observed during 15 March to 8 April 2011 and 4 to 5 March 2013 in the atmosphere above Dome C (Concordia station, Antarctica; 75°06′ S, 123°21′ E; 3233 m a.m.s.l.). The objectives of the paper are mainly to investigate the processes that cause these episodes based on observations and to verify whether operational models can evaluate them. The measurements were obtained from the following instruments: (1) a ground-based microwave radiometer (HAMSTRAD, H2O Antarctica Microwave Stratospheric and Tropospheric Radiometers) installed at Dome C that provided vertical profiles of tropospheric temperature and absolute humidity every 7 min; (2) daily radiosoundings launched at 12:00 UTC at Dome C; (3) a tropospheric aerosol lidar that provides aerosol depolarization ratio along the vertical at Dome C; (4) down- and upward short- and long-wave radiations as provided by the Baseline Surface Radiation Network (BSRN) facilities; (5) an ICE-CAMERA to detect at an hourly rate the size of the ice crystal grains deposited at the surface of the camera; and (6) space-borne aerosol depolarization ratio from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) platform along orbits close to the Dome C station. The time evolution of the atmosphere has also been evaluated by considering the outputs from the mesoscale AROME and the global-scale ARPEGE meteorological models. Thick clouds are detected during the warm and wet periods (24–26 March 2011 and 4 March 2013) with high depolarization ratios (greater than 30 %) from the surface to 5–7 km above the ground associated with precipitation of ice particles and the presence of a supercooled liquid water (depolarization less than 10 %) clouds. Diamond dust and/or ice fog are detected during the cold and dry periods (5 April 2011 and 5 March 2013) with high depolarization ratios (greater than 30 %) in the planetary boundary layer to a maximum altitude of 100–300 m above the ground with little trace of precipitation. Considering 5-day back trajectories, we show that the thick cloud episodes are attributed to air masses with an oceanic origin whilst the diamond dust/ice fog episodes are attributed to air masses with continental origins. Although operational models can reproduce thick cloud episodes in the free troposphere, they cannot evaluate the diamond dust/ice fog episodes in the planetary boundary layer because they require to use more sophisticated cloud and aerosol microphysics schemes.

From 15 March to 8 April 2011 and from 4 to 5 March 2013, the atmosphere above Dome C (Concordia station, Antarctica, 75°06' S, 123°21' E, 3233 m amsl) has been probed by several instruments and model to study episodes of thick cloud and diamond dust (cloud constituted of suspended ice crystals). 1) A ground-based microwave radiometer (HAMSTRAD, H2O Antarctica Microwave Stratospheric and Tropospheric Radiometers) installed at Dome C that provided vertical profiles of tropospheric temperature and absolute humidity to calculate Integrated Water Vapour (IWV). 2) Daily radiosoundings launched at 12:00 UTC at Dome C. 3) A tropospheric aerosol Lidar that provides aerosol depolarization ratio along the vertical at Dome C. 4) Down- and upward short- and longwave radiations as provided by the Baseline Surface Radiation Network (BSRN) facilities. 5) Space-borne aerosol depolarization ratio from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) Lidar aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) platform along orbits close to the Dome C station. The time evolution of the atmosphere has also been evaluated by considering the outputs from the meso-scale AROME and the global-scale ARPEGE meteorological models. Two distinct periods are highlighted by all the datasets: the warm and wet periods (24–26 March 2011 and 4 March 2013) and the cold and dry periods (5 April 2011 and 5 March 2013). Combining radiation and active measurements of aerosols with nebulosity calculations, a thick cloud is detected during the warm and wet periods with high depolarization ratios (greater than 30 %) from the surface to 5–7 km altitude associated with precipitation of ice particles and the presence of a supercooled liquid water (depolarization of about 10 %) cloud. During the cold and dry periods, high depolarization ratios (greater than 30 %) to a maximum altitude of 100–500 m are measured suggesting that the cloud is constituted of ice crystals with no trace of precipitation. These ice crystals in suspension in the air are named diamond dust. Considering 5-day back trajectories from Dome C and global distributions of IWV over the Antarctic show that the thick-cloud episode is attributed to air masses with an oceanic origin whilst the diamond dust episode is attributed to air masses with continental origins. This is consistent with ARPEGE temperature and water vapour tendency favouring predominantly advection processes including microphysical processes for water vapour.

The possibility to discriminate the contribution of the atmosphere and ice clouds by using spectral infrared measurements is a fundamental step to quantify the cloud effect in the climate models. The simultaneous retrieval of clouds and atmospheric parameters allows to take into account the possible correlations between the variables. In this paper we describe the development of a routine able to perform the simultaneous retrieval and its application to the analysis of the spectral measurements acquired by the REFIR-PAD (Radiation Explorer Far Infrared – Prototype for Applications and Development) spectroradiometer, operative from Antarctic Plateau since 2012. This routine is able to operate the retrieval with reduced computing time comparable with the REFIR-PAD data acquisition time. The analysis allowed to retrieve the water vapour and temperature profiles and the clouds optical and micro-physical properties, such as the generalised effective diameter (Dge) and the ice water path (IWP), by exploiting the spectral band between 230–980 cm−1. To simulate the radiative transfer, the LBLRTM (Line By Line Radiative Transfer Model) was integrated with a specific code based on the delta-Eddington two-stream approximation, and further the cirrus clouds single scattering properties were derived from a database for hexagonal column habits. In order to identify the ice clouds a back-scattering and depolarisation lidar was available on the site and allowed to infer the position and the cloud thickness used in the simulations. A climatology of the vertical profiles of water vapour and temperature, was performed by using the daily radiosounding available at the base and it was used to build the a priori and initial guess profiles used in the fitting routine. An optimal estimation method with a Levenberg-Marquardt approach was applied to perform the retrieval. The comparison of results with radiosoundings demonstrates that the retrieved atmospheric state is not disturbed by the clouds presence. Finally, the retrieved clouds parameters were compared with the statistical correlation between the cloud temperature (Tc) and the optical depth measured in Antarctica at Dumond D'Urville and the effective diameters with the ice water content (IWC) obtained in the Arctic region finding a general agreement.

Atmospheric emitted radiance, provided by a FT spectroradiometer installed at Concordia Station, Antarctica in the framework of the COMPASS project has been analyzed providing a characterization of the Antarctic troposphere in the 2014-2016 period.

A retrieval method for cirrus clouds was applied to the measurements of spectral radiance performed by the REFIR-PAD Fourier spectroradiometer over the Antarctic Plateau at Dome C.

An unattended light detection and ranging (LIDAR) operating at 532–1064 nm was used for the continuous monitoring of the planetary boundary layer (PBL) of Florence (Italy). This was the first time that such a well-established remote-sensing technique has been used in Italy as a monitoring tool for the long-term study of urban aerosols: time–height–backscatter plots were used for the interpretation of the PBL dynamics and the vertical distribution of the aerosols, while the aerosol backscatter and its wavelength dependency were used to estimate the mass concentration and the median size of the aerosols 40 m above the ground. The marked wavelength dependency shown by traffic-related aerosols permitted a distinction between fresh urban and background/rural aerosols. In summer, the aerosol mass concentration and the backscatter Angstrom coefficient showed well-defined and very similar daily cycles with a marked peak in the morning and shallow minima in the afternoon. The morning mass peak was produced by small particles (0.05–0.1 μm mode diameter), while there was a prevalence of larger particles in the afternoon. The observed cycles were the result of a coupling between the traffic cycle and the daily surface-wind cycle: fresh urban aerosols produced in town were advected above the LIDAR in the morning by the persisting nighttime breeze. The reversal of the breeze in the late morning was responsible for the low-aerosol concentration observed in the afternoon, when rural air containing a low concentration of relatively large aerosols reached the LIDAR, and dilution of urban aerosol through turbulent mixing occurred. By assuming an exponential decay of aerosol concentration with height, the LIDAR-derived scaling height showed a minimum (100–200 m) in the afternoon, in coincidence with the advection of air from the suburbs. The mass concentration variations were found to be strictly correlated with traffic at night and in the early morning, when the local breeze brought the urban plume above the LIDAR site. The high temporal resolution of the LIDAR made it possible to follow the aerosol mass variations with a 5 min resolution, fast enough to follow the rapid aerosol peak evolution in the morning: the peak mass concentration was 5–10 times larger than during the rest of the day, suggesting the inadequacy of the daily averaged aerosol mass measurements carried out at present by the local authorities.

Contrail backscatter and polarization measurements made using a 532-1064 nm LIDAR in Florence (Italy) indicated that, in most of the cases, the contrail depolarisation and color ratio resemble the usual cirrus. In 20% of the cases, a depolarisation below 15% was observed, both in isolated contrails and in cirrus-embedded contrails. In a few cases, a very low depolarisation, down to 3%, was observed at temperatures in the -40° to -65° C range. In two measurements, a low depolarization was coupled with a high color ratio in the 2-4 range. The low-depolarisation, high color ratio contrail observations are discussed in the light of the results of recent T-matrix scattering simulations. The two events lasted at least 10-20 minutes in the LIDAR data, suggesting a very slow growth or no growth at all of the initial micron-sized contrail particles in the large ice crystals typical of cirrus.

The simulation of the optical properties of ice clouds plays a crucial role in the interpretation of remote sensing data of cirrus clouds. In this work, a novel simulation code (“face tracing”) derived from ray tracing was described and used to compute LIDAR depolarization and the extinction/backscatter ratio at 532 nm, as expected from randomly oriented pristine and slightly deformed hexagonal prisms of various sizes and aspect ratios. By increasing the aspect ratio the depolarization of pristine crystals was found to increase sharply from zero (thin plates) to a maximum value (columns) at an aspect ratio of around 1, where an absolute minimum of extinction/backscatter ratio (corresponding to a maximum LIDAR backscatter efficiency) was also found. When including the far-field diffraction in backscattering simulations, pristine particles smaller than 100 μm showed depolarization and extinction/backscatter ratios comparable with the experimental LIDAR data of cold (T < 30°C) polar cirrus. Recent in situ observations showed the widespread presence of nonpristine hexagonal crystals in cirrus, stimulating the calculation of the backscatter properties of deformed particles by “face tracing.” Simulations for deformed hexagonal prisms showed in most cases a smaller depolarization and a higher extinction/backscatter ratio compared with those obtained for pristine crystals. A mixture containing variable proportions of pristine and deformed hexagonal prisms (with an aspect ratio of 1–2) resulted in a depolarization-extinction/backscatter scatterplot similar to the experimental one for cold polar cirrus.

Based on the hypothesis of a monomodal, lognormal size distribution, the uncertainty affecting the humid-mass retrieval from LIDAR data was estimated by considering our ignorance of the distribution width to be a source of error. The mass to backscatter ratio and its uncertainty were computed for six accumulation-mode aerosol models as a function of the backscatter angstrom coefficient (α) and of the relative humidity (RH). A mass to backscatter uncertainty of less than ±30% was obtained for all six models. We computed the mass and simulated the expected LIDAR backscatter at 532 and 1064 nm for a test data set of 14 “real-world” multimodal size distributions obtained from the literature. The possible presence of 0–20%–50% water-insoluble compounds in each aerosol mode was assumed. An urban-type accumulation mode and 10 different coarse mode compositions were considered, including dust-like aerosols. The aerosol mass concentration was derived by fitting the simulated LIDAR data at 532 and 1064 nm with a monomodal distribution of urban aerosols of “unknown” width. The relative over- or underestimation of the mass with respect to the real aerosol mass was expressed in terms of α and RH for the 10 coarse aerosol types. The LIDAR-derived mass turned out to be underestimated by 0 – 15% in the case of (NH4)2SO4, NaCl, maritime, and H2SO4 coarse aerosols. In the case coarse dust aerosols, the range of underestimation was wider (0–30%). Absorbing aerosols showed a maximum underestimation of 40–50%.

The determination of the mean size distribution for a Type Ib Polar Stratospheric Cloud (“PSC”) has been performed for the first time using extinction/backscattering ratios as obtained from LIDAR data at 355, 532 and 750 nm. The multiwavelength Lidar was operated in Sodankyla, Finland, during the Second European Stratospheric Arctic and Middle-latitudes Experiment (SESAME, November 1994–April 1995). It produced vertical profiles of PSC. Log-normal distributions of supercooled ternary solution (STS), composed of H2SO4–HNO3–H2O particles with mode radius of 0.68–0.9 μm and standard deviation of 1.1–1.4, were retrieved as best fit to experimental data. Laboratory measurements of nr (real part of refractive index), in the 404–633 nm range, show that it depends on the water/acid ratio without any distinction between binary and ternary solutions of nitric and sulphuric acid.

The absence of LIDAR depolarization in a polar cirrus observed above Sodankyla (Finland) showed the presence of spherical particles at −65°C. The presence of pure liquid water is excluded, since homogeneous freezing should occur at or above −40°C. The cirrus layer was detected at the tropopause, during the horizontal and vertical advection above northern Scandinavia of warm and wet oceanic air. Two alternative explanations are suggested, the first one involving the presence of large, deliquescent tropospheric CN, freezing at very low temperature, and the second one involving the presence of metastable, spherical ice-particles produced in the fast adiabatic cooling of the airmasses. The second hypothesis is less reasonable because the absence of depolarized LIDAR signal implies a strict cylindrical symmetry in the particles, a symmetry that is difficult to maintain during the freezing process.

International audience; Polar Stratospheric Cloud (PSC) measurements by ground‐based LIDAR were carried out at Dumont d'Urville, Antarctica, during the years 1989 to 1993. From such measurements it can be seen that there are cases of PSCs that are not consistent with the simplest nitric acid trihydrate (NAT) theories. Several cases of long‐lasting, non‐depolarizing PSCs were detected at temperatures below or close to the NAT freezing threshold, at about 195°K, suggesting the presence of durable supercooled droplets. PSC cases showing depolarizing (frozen) particles well above the NAT expected threshold are also shown. These results seems to be more consistent with recent laboratory and in situ findings, suggesting a close link between sulfate and PSC particles through the HNO3‐H2O‐H2SO4 ternary system. In this framework, non‐depolarizing clouds observed below and close to 195°K would arise from the uptake of HNO3 and water by the background particles before the freezing of the ternary system and the successive growth in nitric‐acid hydrates. Depolarizing “warm” PSCs are also consistent with the laboratory‐observed high melting point of the frozen sulfate core, that remains after NAT evaporation. A problematic PSC case, that cannot be easily explained by this theory is also shown.

Multiwavelength lidar measurements carried out in Sodankyla (Finland, 66°N) during EASOE campaign showed high cirrus clouds growing at the base or within Pinatubo aerosol layer. The temperature was generally below −35°C. The mean peak depolarization at 532 nm for all the campaign was 28%, comparable to the values measured in polar cirrus clouds, observed in Dumont d'Urville (Antarctica, 62°S) during 1989, well before the Pinatubo eruption. Optical depth at 532 nm was smaller than 0.3 (thin cirrus). A wavelength dependency was observed in EASOE cirrus backscattering, suggesting a major presence of submicron and micron-sized particles. Such a presence could explain the low depolarization values.

Tropospheric clouds play a major role in climate regulation but, so far, only a few long-term ground-based observations, devoted to the study of the cloud optical and radiative properties, have been carried out. In this work the statistics of 1 year of coastal Antarctic cloud lidar measurements (532 nm) are shown. Cloud macrophysical and optical parameters have been retrieved from lidar returns; radiosonde data allowed us to build statistics of such quantities in terms of cloud temperature. Information about the physical phase of water and ice crystal habit has been obtained from the depolarization and extinction backscattering ratio; a change in crystal habit (and/or size) around −30°C is evidenced by the depolarization versus temperature behavior. The extinction/backscattering ratio shows a negative trend with temperature, reflecting microphysical changes. Visible extinction shows wide data dispersion, but with a marked negative trend with temperature. The relative derivatives of extinction and optical depth with temperature have been computed, such quantities result quite constant with temperature.

The effect of various errors on the retrieval of optical depth, integrated backscatter, and extinction-to-backscatter ratio in optically thin clouds by use of a two-boundary algorithm is discussed. Uncertainties regarding aerosol loading at the cloud base and top lead to relevant errors that are often larger than those produced by signal noise. Formulas expressing the errors in the lidar-derived optical quantities dependent on optical depth and aerosol uncertainties at the base and top are derived for different fitting procedures. A method for the reduction of errors in the case of consecutive cloud measurements is explored, consisting of the fitting of the retrieved optical-depth-integrated backscatter data to obtain a correct extinction-to-backscatter ratio.

A polarization lidar operating at 532 nm was converted into an automatic, polarimetric lidar capable of measuring the entire Stokes vector of backscattered light and its derived quantities. Among these quantities, circular and linear depolarizations were studied as tools for investigating the presence of anisotropic scattering media. Isotropic scatterers show a simple relationship between linear and circular depolarization, a relation that we confirm theoretically and experimentally. Deviations from this relation, which are possible in the presence of anisotropic scatterers such as horizontally oriented ice plates when they are observed with a slant lidar, were studied both numerically and experimentally.

[1] LIDAR depolarization is commonly used for discriminating liquid and ice particles. Since depolarization depends in a complicated manner on particle shape and size, in-cloud variability of depolarization has been used as an indicator of the microphysical homogeneity of cirrus. The comparison between midlatitude (Florence, Italy, 43. 60°N) and polar (Dumont d'Urville, Antarctica, 66. 68°S) cirrus showed a lower mean depolarization and a higher in-cloud uniformity of cloud depolarization for polar clouds in the (−80, −50°C) temperature range. A wider in-cloud variability of depolarization was observed in polar clouds at higher temperatures (−50, −30°C), reflecting the presence of supercooled liquid layers. The large in-cloud variability of depolarization in Florence cirrus could be explained with a microphysics that is dynamically and chemically perturbed as compared with the polar site. Aged jet contrails are, in fact, present in many Florence cirrus records.

A statistically significant data set of backscattering LIDAR and ground-based information has been obtained for the planetary boundary layer (PBL) of Florence (I). The summer LIDAR backscattering data at 532 and 1064 nm have been used to estimate both the size and the number concentration of the urban aerosols in the accumulation mode. This technique seems to be relatively insensitive to the aerosol composition. The time-height evolution of the PBL [mainly the stable (SL) and the mixed (ML) layers] has been plotted, together with the meteorological and ground-based pollution data for the 200 measurement days. The ground-based hourly pollution data (NOx, CO) have been compared with the hourly-averaged 1064 nm backscattering at 25 meters above the ground. A correlation, R equals 0.65, was obtained between NOx and 1064 nm backscattering during the summer period when the traffic aerosols do not grow considerably after their production. The correlation is not significant during winter, when the growth of the particles is much faster. During winter, the RH variations are more important than aerosol number variations to determine the backscattering evolution.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Consideration is given to a novel inversion algorithm to determine the aerosol size distribution from lidar signals obtained at several wavelengths. This algorithm is based on a nonlinear fit of the backscattered measurements using a set of predetermined functions. Size distribution profiles of tropospheric aerosols in different meteorological conditions - clear, hazy, and cloudy atmosphere - are determined on the basis of lidar measurements made in central Switzerland, which is characterized by a specific microclimate. Measurements of stratospheric clouds and aerosols created by the Pinatubo eruption were measured above Berlin and Sodankyla, Finland. These measurements are used to characterize the size distribution of these volcanic aerosols in order to estimate their influence on radiative transfer.

A fitting procedure for cloud lidar data processing is shown that is based on the computation of the first three moments of the vertical-backscattering (or -extinction) profile. Single-peak clouds or single cloud layers are approximated to asymmetrical Gaussians. The algorithm is particularly stable with respect to noise and processing errors, and it is much faster than the equivalent least-squares approach. Multilayer clouds can easily be treated as a sum of single asymmetrical Gaussian peaks. The method is suitable for cloud-shape parametrization in noisy lidar signatures (like those expected from satellite lidars). It also permits an improvement of cloud radiative-property computations that are based on huge lidar data sets for which storage and careful examination of single lidar profiles can't be carried out.

A multiwavelength lidar operated in Sodankyla, Finland, during the European Arctic Stratospheric Ozone Experiment (December 1991-March 1992). It produced vertical profiles of stratospheric aerosols at four wavelengths. The determination of aerosol mean size distribution has been performed by use of extinction/backscattering ratios as obtained from lidar data processing at 355, 352, and 750 nm. Lognormal distributions of sulfuric particles with mode radius of r(m) = 0.12-0.25 µm and corresponding widths of s = 2-1.6 have been retrieved as best fits of experimental data, in good agreement with in situ measurements. A successful attempt to derive bimodal log-normal distributions is also described, together with the experimental and theoretical problems involved.

As the near-surface atmosphere over the Antarctic Plateau is cold and pristine, its physico-chemical conditions resemble to a certain extent those of the high-troposphere where cirrus clouds form. In this paper, we carry out an observational analysis of two shallow fog clouds forming at cirrus-temperatures - that is, temperatures lower than 235 K - at Dome C, inner Antarctic Plateau. The combination of lidar profiles with temperature and humidity measurements from advanced thermo-hygrometers along a 45-m mast makes it possible to characterise the formation and development of the fog. High supersaturations with respect to ice are observed before the initiation of fog and the values attained suggest that the nucleation process at play is the homogeneous freezing of solution aerosol droplets. To our knowledge, this is the first time that in situ observations show that this nucleation pathway can be at the origin of an ice fog. Once nucleation occurs, the relative humidity gradually decreases down to subsaturated values with respect to ice in a few hours, likely owing to vapour deposition onto ice crystals and turbulent mixing. The development of fog is tightly coupled with the dynamics of the boundary-layer which, in the first study case, experiences a weak diurnal cycle while in the second case, transits from a very stable to a weakly stable dynamical regime. Overall, this paper highlights the potential of the site of Dome C for carrying out observational studies of cloud microphysical processes in natural conditions and using in-situ ground-based instruments.