Articles | Volume 21, issue 3
https://doi.org/10.5194/acp-21-2165-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-2165-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Feb 2021
Research article |
| 15 Feb 2021
| 15 Feb 2021
Quasi-coincident observations of polar stratospheric clouds by ground-based lidar and CALIOP at Concordia (Dome C, Antarctica) from 2014 to 2018
National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), Via Fosso del Cavaliere 100, 00133, Rome, Italy
Francesco Colao
ENEA, Via Enrico Fermi 45, 00044, Frascati, Italy
Francesco Cairo
National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), Via Fosso del Cavaliere 100, 00133, Rome, Italy
Ilir Shuli
National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), Via Fosso del Cavaliere 100, 00133, Rome, Italy
Andrea Scoccione
National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), Via Fosso del Cavaliere 100, 00133, Rome, Italy
Aeronautica Militare, Pratica di Mare, Italy
Mauro De Muro
National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), Via Fosso del Cavaliere 100, 00133, Rome, Italy
Thales Alenia Space, Rome, Italy
Michael Pitts
NASA Langley Research Center, Hampton, Virginia 23681, USA
Lamont Poole
Science Systems and Applications, Inc., Hampton, Virginia 23666, USA
Luca Di Liberto
National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), Via Fosso del Cavaliere 100, 00133, Rome, Italy
Related authors
Francesco Cairo, Martina Krämer, Armin Afchine, Guido Di Donfrancesco, Luca Di Liberto, Sergey Khaykin, Lorenza Lucaferri, Valentin Mitev, Max Port, Christian Rolf, Marcel Snels, Nicole Spelten, Ralf Weigel, and Stephan Borrmann
Atmos. Meas. Tech., 16, 4899–4925, https://doi.org/10.5194/amt-16-4899-2023, https://doi.org/10.5194/amt-16-4899-2023, 2023
Short summary
Short summary
Cirrus clouds have been observed over the Himalayan region between 10 km and the tropopause at 17–18 km. Data from backscattersonde, hygrometers, and particle cloud spectrometers have been compared to assess their consistency. Empirical relationships between optical parameters accessible with remote sensing lidars and cloud microphysical parameters (such as ice water content, particle number and surface area density, and particle aspherical fraction) have been established.
Francesco Cairo, Terry Deshler, Luca Di Liberto, Andrea Scoccione, and Marcel Snels
Atmos. Meas. Tech., 16, 419–431, https://doi.org/10.5194/amt-16-419-2023, https://doi.org/10.5194/amt-16-419-2023, 2023
Short summary
Short summary
The T-matrix theory was used to compute the backscatter and depolarization of mixed-phase PSC, assuming that particles are solid (NAT or possibly ice) above a threshold radius R and liquid (STS) below, and a single shape is common to all solid particles. We used a dataset of coincident lidar and balloon-borne backscattersonde and OPC measurements. The agreement between modelled and measured backscatter is reasonable and allows us to constrain the parameters R and AR.
Francesco Cairo, Terry Deshler, Luca Di Liberto, Andrea Scoccione, and Marcel Snels
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-28, https://doi.org/10.5194/amt-2022-28, 2022
Publication in AMT not foreseen
Short summary
Short summary
We study Mie theory on aspherical scatterers, computing on coincident measurements of PSC by lidar and Particle Counters, the backscatter and depolarization of mixed phase PSC. WParticles are assumed solid if larger than R; for these, Mie results are reduced by C < 1 and only a common fraction X < 1 of the backscattering is polarized. We retrieve R, C and X. The match of model and measurement is good for backscattering, poor for depolarization. The hypothesis on X may be not fulfilled.
Marcel Snels, Stefania Stefani, Angelo Boccaccini, David Biondi, and Giuseppe Piccioni
Atmos. Meas. Tech., 14, 7187–7197, https://doi.org/10.5194/amt-14-7187-2021, https://doi.org/10.5194/amt-14-7187-2021, 2021
Short summary
Short summary
A novel simulation chamber, PASSxS (Planetary Atmosphere Simulation System for Spectroscopy), has been developed for absorption measurements with a Fourier transform spectrometer (FTS) and possibly a cavity ring-down (CRD) spectrometer, with a sample temperature ranging from 100 K up to 550 K, while the pressure of the gas can be varied up to 60 bar. These temperature and pressure ranges cover a significant part of the planetary atmospheres in the solar system and possibly extrasolar planets.
Francesco Cairo, Mauro De Muro, Marcel Snels, Luca Di Liberto, Silvia Bucci, Bernard Legras, Ajil Kottayil, Andrea Scoccione, and Stefano Ghisu
Atmos. Chem. Phys., 21, 7947–7961, https://doi.org/10.5194/acp-21-7947-2021, https://doi.org/10.5194/acp-21-7947-2021, 2021
Short summary
Short summary
A lidar was used in Palau from February–March 2016. Clouds were observed peaking at 3 km below the high cold-point tropopause (CPT). Their occurrence was linked with cold anomalies, while in warm cases, cirrus clouds were restricted to 5 km below the CPT. Thin subvisible cirrus (SVC) near the CPT had distinctive characteristics. They were linked to wave-induced cold anomalies. Back trajectories are mostly compatible with convective outflow, while some distinctive SVC may originate in situ.
Pierre Gramme, Cedric Busschots, Emmanuel Dekemper, Didier Pieroux, Noel C. Baker, Stefano Casadio, Anna Maria lannarelli, Nicola Ferrante, Annalisa Di Bernardino, Paolo Pettinari, Elisa Castelli, Luca di Liberto, and Francesco Cairo
EGUsphere, https://doi.org/10.5194/egusphere-2025-2255, https://doi.org/10.5194/egusphere-2025-2255, 2025
Short summary
Short summary
We present a new remote sensing instrument using hyperspectral imaging to observe the variability in space and time of the nitrogen dioxide concentration. We also show the results of its validation campaign in a challenging urban setting in Rome, showing very good agreement with two reference instruments. Having an imaging instrument rather than the currently state-of-the-art unidirectional spectrometers brings promising capability in the context of satellite products validation.
Francesco Cairo, Martina Krämer, Armin Afchine, Guido Di Donfrancesco, Luca Di Liberto, Sergey Khaykin, Lorenza Lucaferri, Valentin Mitev, Max Port, Christian Rolf, Marcel Snels, Nicole Spelten, Ralf Weigel, and Stephan Borrmann
Atmos. Meas. Tech., 16, 4899–4925, https://doi.org/10.5194/amt-16-4899-2023, https://doi.org/10.5194/amt-16-4899-2023, 2023
Short summary
Short summary
Cirrus clouds have been observed over the Himalayan region between 10 km and the tropopause at 17–18 km. Data from backscattersonde, hygrometers, and particle cloud spectrometers have been compared to assess their consistency. Empirical relationships between optical parameters accessible with remote sensing lidars and cloud microphysical parameters (such as ice water content, particle number and surface area density, and particle aspherical fraction) have been established.
Jason L. Tackett, Jayanta Kar, Mark A. Vaughan, Brian J. Getzewich, Man-Hae Kim, Jean-Paul Vernier, Ali H. Omar, Brian E. Magill, Michael C. Pitts, and David M. Winker
Atmos. Meas. Tech., 16, 745–768, https://doi.org/10.5194/amt-16-745-2023, https://doi.org/10.5194/amt-16-745-2023, 2023
Short summary
Short summary
The accurate identification of aerosol types in the stratosphere is important to characterize their impacts on the Earth climate system. The space-borne lidar on board CALIPSO is well-posed to identify aerosols in the stratosphere from volcanic eruptions and major wildfire events. This paper describes improvements implemented in the version 4.5 CALIPSO data release to more accurately discriminate between volcanic ash, sulfate, and smoke within the stratosphere.
Francesco Cairo, Terry Deshler, Luca Di Liberto, Andrea Scoccione, and Marcel Snels
Atmos. Meas. Tech., 16, 419–431, https://doi.org/10.5194/amt-16-419-2023, https://doi.org/10.5194/amt-16-419-2023, 2023
Short summary
Short summary
The T-matrix theory was used to compute the backscatter and depolarization of mixed-phase PSC, assuming that particles are solid (NAT or possibly ice) above a threshold radius R and liquid (STS) below, and a single shape is common to all solid particles. We used a dataset of coincident lidar and balloon-borne backscattersonde and OPC measurements. The agreement between modelled and measured backscatter is reasonable and allows us to constrain the parameters R and AR.
Clare E. Singer, Benjamin W. Clouser, Sergey M. Khaykin, Martina Krämer, Francesco Cairo, Thomas Peter, Alexey Lykov, Christian Rolf, Nicole Spelten, Armin Afchine, Simone Brunamonti, and Elisabeth J. Moyer
Atmos. Meas. Tech., 15, 4767–4783, https://doi.org/10.5194/amt-15-4767-2022, https://doi.org/10.5194/amt-15-4767-2022, 2022
Short summary
Short summary
In situ measurements of water vapor in the upper troposphere are necessary to study cloud formation and hydration of the stratosphere but challenging due to cold–dry conditions. We compare measurements from three water vapor instruments from the StratoClim campaign in 2017. In clear sky (clouds), point-by-point differences were <1.5±8 % (<1±8 %). This excellent agreement allows detection of fine-scale structures required to understand the impact of convection on stratospheric water vapor.
Sergey M. Khaykin, Elizabeth Moyer, Martina Krämer, Benjamin Clouser, Silvia Bucci, Bernard Legras, Alexey Lykov, Armin Afchine, Francesco Cairo, Ivan Formanyuk, Valentin Mitev, Renaud Matthey, Christian Rolf, Clare E. Singer, Nicole Spelten, Vasiliy Volkov, Vladimir Yushkov, and Fred Stroh
Atmos. Chem. Phys., 22, 3169–3189, https://doi.org/10.5194/acp-22-3169-2022, https://doi.org/10.5194/acp-22-3169-2022, 2022
Short summary
Short summary
The Asian monsoon anticyclone is the key contributor to the global annual maximum in lower stratospheric water vapour. We investigate the impact of deep convection on the lower stratospheric water using a unique set of observations aboard the high-altitude M55-Geophysica aircraft deployed in Nepal in summer 2017 within the EU StratoClim project. We find that convective plumes of wet air can persist within the Asian anticyclone for weeks, thereby enhancing the occurrence of high-level clouds.
Francesco Cairo, Terry Deshler, Luca Di Liberto, Andrea Scoccione, and Marcel Snels
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-28, https://doi.org/10.5194/amt-2022-28, 2022
Publication in AMT not foreseen
Short summary
Short summary
We study Mie theory on aspherical scatterers, computing on coincident measurements of PSC by lidar and Particle Counters, the backscatter and depolarization of mixed phase PSC. WParticles are assumed solid if larger than R; for these, Mie results are reduced by C < 1 and only a common fraction X < 1 of the backscattering is polarized. We retrieve R, C and X. The match of model and measurement is good for backscattering, poor for depolarization. The hypothesis on X may be not fulfilled.
Marcel Snels, Stefania Stefani, Angelo Boccaccini, David Biondi, and Giuseppe Piccioni
Atmos. Meas. Tech., 14, 7187–7197, https://doi.org/10.5194/amt-14-7187-2021, https://doi.org/10.5194/amt-14-7187-2021, 2021
Short summary
Short summary
A novel simulation chamber, PASSxS (Planetary Atmosphere Simulation System for Spectroscopy), has been developed for absorption measurements with a Fourier transform spectrometer (FTS) and possibly a cavity ring-down (CRD) spectrometer, with a sample temperature ranging from 100 K up to 550 K, while the pressure of the gas can be varied up to 60 bar. These temperature and pressure ranges cover a significant part of the planetary atmospheres in the solar system and possibly extrasolar planets.
Christoph Mahnke, Ralf Weigel, Francesco Cairo, Jean-Paul Vernier, Armin Afchine, Martina Krämer, Valentin Mitev, Renaud Matthey, Silvia Viciani, Francesco D'Amato, Felix Ploeger, Terry Deshler, and Stephan Borrmann
Atmos. Chem. Phys., 21, 15259–15282, https://doi.org/10.5194/acp-21-15259-2021, https://doi.org/10.5194/acp-21-15259-2021, 2021
Short summary
Short summary
In 2017, in situ aerosol measurements were conducted aboard the M55 Geophysica in the Asian monsoon region. The vertical particle mixing ratio profiles show a distinct layer (15–18.5 km), the Asian tropopause aerosol layer (ATAL). The backscatter ratio (BR) was calculated based on the aerosol size distributions and compared with the BRs detected by a backscatter probe and a lidar aboard M55, and by the CALIOP lidar. All four methods show enhanced BRs in the ATAL altitude range (max. at 17.5 km).
Francesco Cairo, Mauro De Muro, Marcel Snels, Luca Di Liberto, Silvia Bucci, Bernard Legras, Ajil Kottayil, Andrea Scoccione, and Stefano Ghisu
Atmos. Chem. Phys., 21, 7947–7961, https://doi.org/10.5194/acp-21-7947-2021, https://doi.org/10.5194/acp-21-7947-2021, 2021
Short summary
Short summary
A lidar was used in Palau from February–March 2016. Clouds were observed peaking at 3 km below the high cold-point tropopause (CPT). Their occurrence was linked with cold anomalies, while in warm cases, cirrus clouds were restricted to 5 km below the CPT. Thin subvisible cirrus (SVC) near the CPT had distinctive characteristics. They were linked to wave-induced cold anomalies. Back trajectories are mostly compatible with convective outflow, while some distinctive SVC may originate in situ.
Luca Ferrero, Asta Gregorič, Griša Močnik, Martin Rigler, Sergio Cogliati, Francesca Barnaba, Luca Di Liberto, Gian Paolo Gobbi, Niccolò Losi, and Ezio Bolzacchini
Atmos. Chem. Phys., 21, 4869–4897, https://doi.org/10.5194/acp-21-4869-2021, https://doi.org/10.5194/acp-21-4869-2021, 2021
Short summary
Short summary
The work experimentally quantifies the impact of cloudiness and cloud type on the atmospheric heating rate of black and brown carbon. The most impacting clouds were stratocumulus, altostratus and stratus. Clouds caused a decrease of the heating rate of about 12 % per okta. The black carbon decease was slightly higher with respect to that of brown carbon. This study highlights the need to take into account the role of cloudiness when modelling light-absorbing aerosol climate forcing.
Michael Steiner, Beiping Luo, Thomas Peter, Michael C. Pitts, and Andrea Stenke
Geosci. Model Dev., 14, 935–959, https://doi.org/10.5194/gmd-14-935-2021, https://doi.org/10.5194/gmd-14-935-2021, 2021
Short summary
Short summary
We evaluate polar stratospheric clouds (PSCs) as simulated by the chemistry–climate model (CCM) SOCOLv3.1 in comparison with measurements by the CALIPSO satellite. A cold bias results in an overestimated PSC area and mountain-wave ice is underestimated, but we find overall good temporal and spatial agreement of PSC occurrence and composition. This work confirms previous studies indicating that simplified PSC schemes may also achieve good approximations of the fundamental properties of PSCs.
Matthias Tesche, Peggy Achtert, and Michael C. Pitts
Atmos. Chem. Phys., 21, 505–516, https://doi.org/10.5194/acp-21-505-2021, https://doi.org/10.5194/acp-21-505-2021, 2021
Short summary
Short summary
We combine spaceborne lidar observations of clouds in the troposphere and stratosphere to assess the outcome of ground-based polar stratospheric cloud (PSC) observations that are often performed at the mercy of tropospheric clouds. We find that the outcome of ground-based lidar measurements of PSCs depends on the location of the measurement. We also provide recommendations regarding the most suitable sites in the Arctic and Antarctic.
Silvia Bucci, Bernard Legras, Pasquale Sellitto, Francesco D'Amato, Silvia Viciani, Alessio Montori, Antonio Chiarugi, Fabrizio Ravegnani, Alexey Ulanovsky, Francesco Cairo, and Fred Stroh
Atmos. Chem. Phys., 20, 12193–12210, https://doi.org/10.5194/acp-20-12193-2020, https://doi.org/10.5194/acp-20-12193-2020, 2020
Short summary
Short summary
The paper presents and evaluates a transport analysis method to study the convective injection of air in the upper troposphere–lower stratosphere of the Asian monsoon anticyclone region. The approach is thereby used to analyse the trace gas data collected during the StratoClim aircraft campaign. The results showed that fresh convective air can be injected fast at a high level of the atmosphere (above 17 km), with potential impacts on the stratospheric chemistry of the Northern Hemisphere.
Cited articles
Achtert, P. and Tesche, M.: Assessing lidar-based classification schemes for
polar stratospheric clouds based on 16 years of measurements at Esrange,
Sweden, J. Geophys. Res.-Atmos., 119, 1386–1405,
https://doi.org/10.1002/2013JD020355, 2014. a
Achtert, P., Khosrawi, F., Blum, U., and Fricke, K. H.: Investigation of polar
stratospheric clouds in January 2008 by means of ground-based and spaceborne
lidar measurements and microphysical box model simulations, J. Geophys. Res.-Atmos., 116, D07201, https://doi.org/10.1029/2010JD014803, 2011. a, b
Adriani, A., Deshler, T., Gobbi, G. P., Johnson, B. J., and Di Donfrancesco,
G.: Polar stratospheric clouds over McMurdo, Antarctica, during the 1991
spring: Lidar and particle counter measurements, Geophys. Res.
Lett., 19, 1755–1758, https://doi.org/10.1029/92GL01941, 1992. a
Adriani, A., Deshler, T., Di Donfrancesco, G., and Gobbi, G.: Polar
stratospheric clouds and volcanic aerosol during spring 1992 over McMurdo
Station, Antarctica: Lidar and particle counter comparative measurements,
J. Geophys. Res.-Atmos., 100, 25877–25897, 1995. a
Adriani, A., Massoli, P., Di Donfrancesco, G., Cairo, F., Moriconi, M., and
Snels, M.: Climatology of polar stratospheric clouds based on lidar
observations from 1993 to 2001 over McMurdo Station, Antarctica, J.
Geophys. Res.-Atmos., 109, D24211, https://doi.org/10.1029/2004JD004800,
2004. a
Behrendt, A. and Nakamura, T.: Calculation of the calibration constant of
polarization lidar and its dependency on atmospheric temperature, Opt.
Express, 10, 805–817, https://doi.org/10.1364/OE.10.000805, 2002. a
Campbell, J. R. and Sassen, K.: Polar stratospheric clouds at the South Pole
from 5 years of continuous lidar data: Macrophysical, optical, and
thermodynamic properties, J. Geophys. Res.-Atmos.,
113, D20204, https://doi.org/10.1029/2007JD009680, 2008. a
David, C., Bekki, S., Godin, S., Megie, G., and Chipperfield, M.: Polar
stratospheric clouds climatology over Dumont d'Urville between 1989 and 1993
and the influence of volcanic aerosols on their formation, J.
Geophys. Res.-Atmos., 103, 22163–22180,
https://doi.org/10.1029/98JD01692, 1998. a
David, C., Keckhut, P., Armetta, A., Jumelet, J., Snels, M., Marchand, M., and Bekki, S.: Radiosonde stratospheric temperatures at Dumont d'Urville (Antarctica): trends and link with polar stratospheric clouds, Atmos. Chem. Phys., 10, 3813–3825, https://doi.org/10.5194/acp-10-3813-2010, 2010. a
David, C., Haefele, A., Keckhut, P., Marchand, M., Jumelet, J., Leblanc, T.,
Cenac, C., Laqui, C., Porteneuve, J., Haeffelin, M., Courcoux, Y., Snels, M.,
Viterbini, M., and Quatrevalet, M.: Evaluation of stratospheric ozone,
temperature, and aerosol profiles from the LOANA lidar in Antarctica, Polar
Sci., 6, 209–225, https://doi.org/10.1016/j.polar.2012.07.001,
2012. a
Di Liberto, L., Cairo, F., Fierli, F., Di Donfrancesco, G., Viterbini, M.,
Deshler, T., and Snels, M.: Observation of polar stratospheric clouds over
McMurdo (77.85∘ S, 166.67∘ E) (2006–2010), J. Geophys. Res.-Atmos., 119, 5528–5541, https://doi.org/10.1002/2013JD019892, 2014. a
Fiocco, G., Cacciani, M., Di Girolamo, P., and Fua, D.: Stratospheric clouds
at South-Pole during 1988 .1. Results of lidar observations and their
relationship to temperature, J. Geophys. Res.-Atmos.,
97, 5939–5946, 1992. a
Fua, D., Cacciani, M., Di Girolamo, P., Fiocco, G., and Disarra, A.:
Stratospheric clouds at South-Pole during 1988 .2. Their evolution in
relation to atmospheric structure and composition, J.
Res.-Atmos., 97, 5947–5952, 1992. a
Gobbi, G.: Lidar estimation of stratospheric aerosol properties – surface,
volume, and extinction to backscatter ratio, J. Geophys.
Res.-Atmos., 100, 11219–11235, https://doi.org/10.1029/94JD03106,
1995. a
Hanson, D. and Mauersberger, K.: Laboratory studies of the nitric acid
trihydrate: Implications for the south polar stratosphere, Geophys.
Res. Lett., 15, 855–858, https://doi.org/10.1029/GL015i008p00855, 1988. a
Huang, W., Chu, X., Simpson, S. E., Nott, G. J., and Espy, P. J.: Polar Stratospheric Clouds Observed by Lidar in Antarctica and the Effect of Polar Vortex, AGU Spring Meeting Acapulco, Guerrero, Mexico, 22–25 May 2007, Eos Trans. AGU, 88, Jt. Assembly. Suppl., Abstract A53A-07, 2007. a
Hunt, W. H., Winker, D. M., Vaughan, M. A., Powell, K. A., Lucker, P. L., and
Weimer, C.: CALIPSO lidar description and performance assessment, J.
Atmos. Ocean. Tech., 26, 1214–1228,
https://doi.org/10.1175/2009JTECHA1223.1, 2009. a
Klett, J. D.: Stable analytical inversion solution for processing lidar
returns, Appl. Optics, 20, 211–220, https://doi.org/10.1364/AO.20.000211, 1981. a
Pitts, M. C., Poole, L. R., and Thomason, L. W.: CALIPSO polar stratospheric cloud observations: second-generation detection algorithm and composition discrimination, Atmos. Chem. Phys., 9, 7577–7589, https://doi.org/10.5194/acp-9-7577-2009, 2009. a
Pitts, M. C., Poole, L. R., Dörnbrack, A., and Thomason, L. W.: The 2009–2010 Arctic polar stratospheric cloud season: a CALIPSO perspective, Atmos. Chem. Phys., 11, 2161–2177, https://doi.org/10.5194/acp-11-2161-2011, 2011. a
Pitts, M. C., Poole, L. R., Lambert, A., and Thomason, L. W.: An assessment of CALIOP polar stratospheric cloud composition classification, Atmos. Chem. Phys., 13, 2975–2988, https://doi.org/10.5194/acp-13-2975-2013, 2013.
a
Pitts, M. C., Poole, L. R., and Gonzalez, R.: Polar stratospheric cloud climatology based on CALIPSO spaceborne lidar measurements from 2006 to 2017, Atmos. Chem. Phys., 18, 10881–10913, https://doi.org/10.5194/acp-18-10881-2018, 2018. a, b, c, d
Santacesaria, V., MacKenzie, A. R., and Stefanutti, L.: A climatological study
of polar stratospheric clouds (1989–1997) from LIDAR measurements over
Dumont d'Urville (Antarctica), Tellus B, 53, 306–321,
https://doi.org/10.1034/j.1600-0889.2001.01155.x, 2001. a
Simpson, S. E., Chu, X., Liu, A., Robinson, W., J. Nott, G., Diettrich, J., Espy, P., and Shanklin, J.: Polar stratospheric clouds observed by a lidar at Rothera, Antarctica (67.5∘ S, 68.0∘ W), in:
SPIE Proceedings volume 5887, Optics and Photonics 2005, 31 July–4 August 2005, San Diego, California, United States, https://doi.org/10.1117/12.620399, 2005. a
Snels, M., Cairo, F., Colao, F., and Di Donfrancesco, G.: Calibration method
for depolarization lidar measurements, Int. J. Remote
Sens., 30, 5725–5736, https://doi.org/10.1080/01431160902729572, 2009. a
Snels, M., Scoccione, A., Di Liberto, L., Colao, F., Pitts, M., Poole, L., Deshler, T., Cairo, F., Cagnazzo, C., and Fierli, F.: Comparison of Antarctic polar stratospheric cloud observations by ground-based and space-borne lidar and relevance for chemistry–climate models, Atmos. Chem. Phys., 19, 955–972, https://doi.org/10.5194/acp-19-955-2019, 2019. a, b, c, d, e
Stephens, G., Winker, D., Pelon, J., Trepte, C., Vane, D., Yuhas, C., L'Ecuyer,
T., and Lebsock, M.: CloudSat and CALIPSO within the A-Train: Ten years of
actively observing the Earth system, B. Am. Meteorol.
Soc., 99, 569–581, https://doi.org/10.1175/BAMS-D-16-0324.1, 2018. a
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z.,
Illingworth, A. J., O'Connor, E. J., Rossow, W. B., Durden, S. L., Miller,
S. D., Austin, R. T., Benedetti, A., Mitrescu, C., and Team, T. C. S.: The
cloudsat mission and the A-train, B. Am. Meteorol.
Soc., 83, 1771–1790, https://doi.org/10.1175/BAMS-83-12-1771, 2002. a
Tesche, M., Achtert, P., and Pitts, M. C.: On the best locations for ground-based polar stratospheric cloud (PSC) observations, Atmos. Chem. Phys., 21, 505–516, https://doi.org/10.5194/acp-21-505-2021, 2021. a, b
Waugh, D. W. and Randel, W. J.: Climatology of Arctic and Antarctic Polar
Vortices Using Elliptical Diagnostics, J. Atmos. Sci.,
56, 1594–1613, https://doi.org/10.1175/1520-0469(1999)056<1594:COAAAP>2.0.CO;2, 1999. a
Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., Hunt,
W. H., and Young, S. A.: Overview of the CALIPSO mission and CALIOP data
processing algorithms, J. Atmos. Ocean. Tech., 26,
2310–2323, https://doi.org/10.1175/2009JTECHA1281.1, 2009. a
Short summary
A total of 5 years of polar stratospheric cloud (PSC) observations by ground-based lidar at Concordia station (Antarctica) are presented. These data have been recorded in coincidence with the overpasses of the CALIOP lidar on the CALIPSO satellite. First we demonstrate that both lidars observe essentially the same thing, in terms of detection and composition of the PSCs. Then we use both datasets to study seasonal and interannual variations in the formation temperature of NAT mixtures.
A total of 5 years of polar stratospheric cloud (PSC) observations by ground-based lidar at...
Altmetrics
Final-revised paper
Preprint