Articles | Volume 6, issue 2
https://doi.org/10.5194/amt-6-457-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-6-457-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
22 Feb 2013
Research article |
| 22 Feb 2013
Cirrus crystal fall velocity estimates using the Match method with ground-based lidars: first investigation through a case study
D. Dionisi
Laboratoire Atmospheres, Milieux, Observations Spatiales-IPSL, UMR8190, CNRS/INSU, UVSQ-UPMC, UniverSud Paris, Guyancourt, France
Istituto di Scienze dell'Atmosfera e del Clima, Consiglio Nazionale delle Ricerche, Roma, Italy
P. Keckhut
Laboratoire Atmospheres, Milieux, Observations Spatiales-IPSL, UMR8190, CNRS/INSU, UVSQ-UPMC, UniverSud Paris, Guyancourt, France
C. Hoareau
LMD, UMR8539, INSU-CNRS, UPMC, Ecole Polytechnique, 91128, Palaiseau Cedex, France
N. Montoux
Laboratoire de Meteorologie Physique, Blaise Pascal University, Aubiere, France
F. Congeduti
Istituto di Scienze dell'Atmosfera e del Clima, Consiglio Nazionale delle Ricerche, Roma, Italy
Related authors
Alexandra Tsekeri, Anna Gialitaki, Marco Di Paolantonio, Davide Dionisi, Gian Luigi Liberti, Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk, Daniel Pérez-Ramírez, Maria J. Granados Muñoz, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Diego Bermejo Pantaleón, Juan Antonio Bravo-Aranda, Anna Kampouri, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Salvatore Romano, Maria Rita Perrone, Xiaoxia Shang, Mika Komppula, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Diofantos Hadjimitsis, Francisco Navas-Guzmán, Alexander Haefele, Dominika Szczepanik, Artur Tomczak, Iwona S. Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athena A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 16, 6025–6050, https://doi.org/10.5194/amt-16-6025-2023, https://doi.org/10.5194/amt-16-6025-2023, 2023
Short summary
Short summary
EARLINET/ACTRIS organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. The work presented herein focuses on deriving a common methodology for applying a synergistic retrieval that utilizes the network's ground-based passive and active remote sensing measurements and deriving the aerosols from anthropogenic activities over Europe.
Marco Di Paolantonio, Davide Dionisi, and Gian Luigi Liberti
Atmos. Meas. Tech., 15, 1217–1231, https://doi.org/10.5194/amt-15-1217-2022, https://doi.org/10.5194/amt-15-1217-2022, 2022
Short summary
Short summary
A procedure for the characterization of the lidar transmitter–receiver geometry was developed. This characterization is currently implemented in the Rome RMR lidar to optimize the telescope/beam alignment, retrieve the overlap function, and estimate the absolute and relative tilt of the laser beam. This procedure can be potentially used to complement the standard EARLINET quality assurance tests.
Holger Baars, Albert Ansmann, Kevin Ohneiser, Moritz Haarig, Ronny Engelmann, Dietrich Althausen, Ingrid Hanssen, Michael Gausa, Aleksander Pietruczuk, Artur Szkop, Iwona S. Stachlewska, Dongxiang Wang, Jens Reichardt, Annett Skupin, Ina Mattis, Thomas Trickl, Hannes Vogelmann, Francisco Navas-Guzmán, Alexander Haefele, Karen Acheson, Albert A. Ruth, Boyan Tatarov, Detlef Müller, Qiaoyun Hu, Thierry Podvin, Philippe Goloub, Igor Veselovskii, Christophe Pietras, Martial Haeffelin, Patrick Fréville, Michaël Sicard, Adolfo Comerón, Alfonso Javier Fernández García, Francisco Molero Menéndez, Carmen Córdoba-Jabonero, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Daniele Bortoli, Maria João Costa, Davide Dionisi, Gian Luigi Liberti, Xuan Wang, Alessia Sannino, Nikolaos Papagiannopoulos, Antonella Boselli, Lucia Mona, Giuseppe D'Amico, Salvatore Romano, Maria Rita Perrone, Livio Belegante, Doina Nicolae, Ivan Grigorov, Anna Gialitaki, Vassilis Amiridis, Ourania Soupiona, Alexandros Papayannis, Rodanthi-Elisaveth Mamouri, Argyro Nisantzi, Birgit Heese, Julian Hofer, Yoav Y. Schechner, Ulla Wandinger, and Gelsomina Pappalardo
Atmos. Chem. Phys., 19, 15183–15198, https://doi.org/10.5194/acp-19-15183-2019, https://doi.org/10.5194/acp-19-15183-2019, 2019
Emmanouil Proestakis, Vassilis Amiridis, Eleni Marinou, Ioannis Binietoglou, Albert Ansmann, Ulla Wandinger, Julian Hofer, John Yorks, Edward Nowottnick, Abduvosit Makhmudov, Alexandros Papayannis, Aleksander Pietruczuk, Anna Gialitaki, Arnoud Apituley, Artur Szkop, Constantino Muñoz Porcar, Daniele Bortoli, Davide Dionisi, Dietrich Althausen, Dimitra Mamali, Dimitris Balis, Doina Nicolae, Eleni Tetoni, Gian Luigi Liberti, Holger Baars, Ina Mattis, Iwona Sylwia Stachlewska, Kalliopi Artemis Voudouri, Lucia Mona, Maria Mylonaki, Maria Rita Perrone, Maria João Costa, Michael Sicard, Nikolaos Papagiannopoulos, Nikolaos Siomos, Pasquale Burlizzi, Rebecca Pauly, Ronny Engelmann, Sabur Abdullaev, and Gelsomina Pappalardo
Atmos. Chem. Phys., 19, 11743–11764, https://doi.org/10.5194/acp-19-11743-2019, https://doi.org/10.5194/acp-19-11743-2019, 2019
Short summary
Short summary
To increase accuracy and validate satellite-based products, comparison with ground-based reference observations is required. To do this, we present evaluation activity of EARLINET for the qualitative and quantitative assessment of NASA's CATS lidar operating aboard the International Space Station (ISS) while identified discrepancies are discussed. Better understanding CATS performance and limitations provides a valuable basis for scientific studies implementing the satellite-based lidar system.
Henri Diémoz, Francesca Barnaba, Tiziana Magri, Giordano Pession, Davide Dionisi, Sara Pittavino, Ivan K. F. Tombolato, Monica Campanelli, Lara Sofia Della Ceca, Maxime Hervo, Luca Di Liberto, Luca Ferrero, and Gian Paolo Gobbi
Atmos. Chem. Phys., 19, 3065–3095, https://doi.org/10.5194/acp-19-3065-2019, https://doi.org/10.5194/acp-19-3065-2019, 2019
Short summary
Short summary
We assess the impact of air masses transported from the Po basin on the particulate matter (PM) levels in the northwestern Alps using multi-sensor observations from ground and space, and models. In this part 1 of the study, we investigate the phenomenon through three selected case studies representative of different seasons. We show that advected aerosols remarkably degrade the air quality of the Alpine area (PM10 increasing up to >100 µg m−3) and we discuss the measurement–model discrepancies.
Davide Dionisi, Francesca Barnaba, Henri Diémoz, Luca Di Liberto, and Gian Paolo Gobbi
Atmos. Meas. Tech., 11, 6013–6042, https://doi.org/10.5194/amt-11-6013-2018, https://doi.org/10.5194/amt-11-6013-2018, 2018
Francesca Costabile, Stefania Gilardoni, Francesca Barnaba, Antonio Di Ianni, Luca Di Liberto, Davide Dionisi, Maurizio Manigrasso, Marco Paglione, Vanes Poluzzi, Matteo Rinaldi, Maria Cristina Facchini, and Gian Paolo Gobbi
Atmos. Chem. Phys., 17, 313–326, https://doi.org/10.5194/acp-17-313-2017, https://doi.org/10.5194/acp-17-313-2017, 2017
Short summary
Short summary
We investigate the particle size distribution and spectral optical properties of brown carbon (BrC) associated with the formation of secondary aerosol in the ambient atmosphere and relate these properties to major aerosol chemical components. We found that BrC occurs in particles in the droplet mode size range, enriched in ammonium nitrate and poor in black carbon (BC), with a strong dependance on the organic aerosol to BC ratio.
Umberto Rizza, Francesca Barnaba, Mario Marcello Miglietta, Cristina Mangia, Luca Di Liberto, Davide Dionisi, Francesca Costabile, Fabio Grasso, and Gian Paolo Gobbi
Atmos. Chem. Phys., 17, 93–115, https://doi.org/10.5194/acp-17-93-2017, https://doi.org/10.5194/acp-17-93-2017, 2017
J.-L. Baray, Y. Courcoux, P. Keckhut, T. Portafaix, P. Tulet, J.-P. Cammas, A. Hauchecorne, S. Godin Beekmann, M. De Mazière, C. Hermans, F. Desmet, K. Sellegri, A. Colomb, M. Ramonet, J. Sciare, C. Vuillemin, C. Hoareau, D. Dionisi, V. Duflot, H. Vérèmes, J. Porteneuve, F. Gabarrot, T. Gaudo, J.-M. Metzger, G. Payen, J. Leclair de Bellevue, C. Barthe, F. Posny, P. Ricaud, A. Abchiche, and R. Delmas
Atmos. Meas. Tech., 6, 2865–2877, https://doi.org/10.5194/amt-6-2865-2013, https://doi.org/10.5194/amt-6-2865-2013, 2013
Alexandra Tsekeri, Anna Gialitaki, Marco Di Paolantonio, Davide Dionisi, Gian Luigi Liberti, Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk, Daniel Pérez-Ramírez, Maria J. Granados Muñoz, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Diego Bermejo Pantaleón, Juan Antonio Bravo-Aranda, Anna Kampouri, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Salvatore Romano, Maria Rita Perrone, Xiaoxia Shang, Mika Komppula, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Diofantos Hadjimitsis, Francisco Navas-Guzmán, Alexander Haefele, Dominika Szczepanik, Artur Tomczak, Iwona S. Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athena A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 16, 6025–6050, https://doi.org/10.5194/amt-16-6025-2023, https://doi.org/10.5194/amt-16-6025-2023, 2023
Short summary
Short summary
EARLINET/ACTRIS organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. The work presented herein focuses on deriving a common methodology for applying a synergistic retrieval that utilizes the network's ground-based passive and active remote sensing measurements and deriving the aerosols from anthropogenic activities over Europe.
Mathieu Ratynski, Sergey Khaykin, Alain Hauchecorne, Robin Wing, Jean-Pierre Cammas, Yann Hello, and Philippe Keckhut
Atmos. Meas. Tech., 16, 997–1016, https://doi.org/10.5194/amt-16-997-2023, https://doi.org/10.5194/amt-16-997-2023, 2023
Short summary
Short summary
Aeolus is the first spaceborne wind lidar providing global wind measurements since 2018. This study offers a comprehensive analysis of Aeolus instrument performance, using ground-based wind lidars and meteorological radiosondes, at tropical and mid-latitudes sites. The analysis allows assessing the long-term evolution of the satellite's performance for more than 3 years. The results will help further elaborate the understanding of the error sources and the behavior of the Doppler wind lidar.
Marco Di Paolantonio, Davide Dionisi, and Gian Luigi Liberti
Atmos. Meas. Tech., 15, 1217–1231, https://doi.org/10.5194/amt-15-1217-2022, https://doi.org/10.5194/amt-15-1217-2022, 2022
Short summary
Short summary
A procedure for the characterization of the lidar transmitter–receiver geometry was developed. This characterization is currently implemented in the Rome RMR lidar to optimize the telescope/beam alignment, retrieve the overlap function, and estimate the absolute and relative tilt of the laser beam. This procedure can be potentially used to complement the standard EARLINET quality assurance tests.
Stephanie Evan, Jerome Brioude, Karen Rosenlof, Sean M. Davis, Holger Vömel, Damien Héron, Françoise Posny, Jean-Marc Metzger, Valentin Duflot, Guillaume Payen, Hélène Vérèmes, Philippe Keckhut, and Jean-Pierre Cammas
Atmos. Chem. Phys., 20, 10565–10586, https://doi.org/10.5194/acp-20-10565-2020, https://doi.org/10.5194/acp-20-10565-2020, 2020
Short summary
Short summary
The role of deep convection in the southwest Indian Ocean (the 3rd most active tropical cyclone basin) on the composition of the tropical tropopause layer (TTL) and the climate system is less understood due to scarce observations. Balloon-borne lidar and satellite measurements in the southwest Indian Ocean were used to study tropical cyclones' influence on TTL composition. This study compares the impact of a tropical storm and cyclone on the humidification of the TTL over the SW Indian Ocean.
Holger Baars, Albert Ansmann, Kevin Ohneiser, Moritz Haarig, Ronny Engelmann, Dietrich Althausen, Ingrid Hanssen, Michael Gausa, Aleksander Pietruczuk, Artur Szkop, Iwona S. Stachlewska, Dongxiang Wang, Jens Reichardt, Annett Skupin, Ina Mattis, Thomas Trickl, Hannes Vogelmann, Francisco Navas-Guzmán, Alexander Haefele, Karen Acheson, Albert A. Ruth, Boyan Tatarov, Detlef Müller, Qiaoyun Hu, Thierry Podvin, Philippe Goloub, Igor Veselovskii, Christophe Pietras, Martial Haeffelin, Patrick Fréville, Michaël Sicard, Adolfo Comerón, Alfonso Javier Fernández García, Francisco Molero Menéndez, Carmen Córdoba-Jabonero, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Daniele Bortoli, Maria João Costa, Davide Dionisi, Gian Luigi Liberti, Xuan Wang, Alessia Sannino, Nikolaos Papagiannopoulos, Antonella Boselli, Lucia Mona, Giuseppe D'Amico, Salvatore Romano, Maria Rita Perrone, Livio Belegante, Doina Nicolae, Ivan Grigorov, Anna Gialitaki, Vassilis Amiridis, Ourania Soupiona, Alexandros Papayannis, Rodanthi-Elisaveth Mamouri, Argyro Nisantzi, Birgit Heese, Julian Hofer, Yoav Y. Schechner, Ulla Wandinger, and Gelsomina Pappalardo
Atmos. Chem. Phys., 19, 15183–15198, https://doi.org/10.5194/acp-19-15183-2019, https://doi.org/10.5194/acp-19-15183-2019, 2019
Aurélien Chauvigné, Diego Aliaga, Karine Sellegri, Nadège Montoux, Radovan Krejci, Griša Močnik, Isabel Moreno, Thomas Müller, Marco Pandolfi, Fernando Velarde, Kay Weinhold, Patrick Ginot, Alfred Wiedensohler, Marcos Andrade, and Paolo Laj
Atmos. Chem. Phys., 19, 14805–14824, https://doi.org/10.5194/acp-19-14805-2019, https://doi.org/10.5194/acp-19-14805-2019, 2019
Short summary
Short summary
The study presents for the first time the analysis of aerosol optical properties at the unique high-altitude station of Chacaltaya, Bolivia. Ideally located, the station allows us to better understand influences of urban areas and the Amazon Forest on tropospheric properties. An emerging method is applied to characterize aerosol origins and permits us to illustrate evidence of natural and anthropogenic influences.
Marie Lothon, Paul Barnéoud, Omar Gabella, Fabienne Lohou, Solène Derrien, Sylvain Rondi, Marjolaine Chiriaco, Sophie Bastin, Jean-Charles Dupont, Martial Haeffelin, Jordi Badosa, Nicolas Pascal, and Nadège Montoux
Atmos. Meas. Tech., 12, 5519–5534, https://doi.org/10.5194/amt-12-5519-2019, https://doi.org/10.5194/amt-12-5519-2019, 2019
Short summary
Short summary
In the context of an atmospheric network of instrumented sites equipped with sky cameras for cloud monitoring, we present an algorithm named ELIFAN, which aims to estimate the cloud cover amount from full-sky visible daytime images. ELIFAN is based on red-to-blue ratio thresholding applied on the image pixels and on the use of a blue-sky library. We present its principle and its performance and highlight the interest of combining several complementary instruments.
Emmanouil Proestakis, Vassilis Amiridis, Eleni Marinou, Ioannis Binietoglou, Albert Ansmann, Ulla Wandinger, Julian Hofer, John Yorks, Edward Nowottnick, Abduvosit Makhmudov, Alexandros Papayannis, Aleksander Pietruczuk, Anna Gialitaki, Arnoud Apituley, Artur Szkop, Constantino Muñoz Porcar, Daniele Bortoli, Davide Dionisi, Dietrich Althausen, Dimitra Mamali, Dimitris Balis, Doina Nicolae, Eleni Tetoni, Gian Luigi Liberti, Holger Baars, Ina Mattis, Iwona Sylwia Stachlewska, Kalliopi Artemis Voudouri, Lucia Mona, Maria Mylonaki, Maria Rita Perrone, Maria João Costa, Michael Sicard, Nikolaos Papagiannopoulos, Nikolaos Siomos, Pasquale Burlizzi, Rebecca Pauly, Ronny Engelmann, Sabur Abdullaev, and Gelsomina Pappalardo
Atmos. Chem. Phys., 19, 11743–11764, https://doi.org/10.5194/acp-19-11743-2019, https://doi.org/10.5194/acp-19-11743-2019, 2019
Short summary
Short summary
To increase accuracy and validate satellite-based products, comparison with ground-based reference observations is required. To do this, we present evaluation activity of EARLINET for the qualitative and quantitative assessment of NASA's CATS lidar operating aboard the International Space Station (ISS) while identified discrepancies are discussed. Better understanding CATS performance and limitations provides a valuable basis for scientific studies implementing the satellite-based lidar system.
Henri Diémoz, Francesca Barnaba, Tiziana Magri, Giordano Pession, Davide Dionisi, Sara Pittavino, Ivan K. F. Tombolato, Monica Campanelli, Lara Sofia Della Ceca, Maxime Hervo, Luca Di Liberto, Luca Ferrero, and Gian Paolo Gobbi
Atmos. Chem. Phys., 19, 3065–3095, https://doi.org/10.5194/acp-19-3065-2019, https://doi.org/10.5194/acp-19-3065-2019, 2019
Short summary
Short summary
We assess the impact of air masses transported from the Po basin on the particulate matter (PM) levels in the northwestern Alps using multi-sensor observations from ground and space, and models. In this part 1 of the study, we investigate the phenomenon through three selected case studies representative of different seasons. We show that advected aerosols remarkably degrade the air quality of the Alpine area (PM10 increasing up to >100 µg m−3) and we discuss the measurement–model discrepancies.
Robin Wing, Alain Hauchecorne, Philippe Keckhut, Sophie Godin-Beekmann, Sergey Khaykin, and Emily M. McCullough
Atmos. Meas. Tech., 11, 6703–6717, https://doi.org/10.5194/amt-11-6703-2018, https://doi.org/10.5194/amt-11-6703-2018, 2018
Short summary
Short summary
We have compared 2433 nights of OHP lidar temperatures (2002–2018) to temperatures derived from the satellites SABER and MLS. We have found a winter stratopause cold bias in the satellite measurements with respect to the lidar (−6 K for SABER and −17 K for MLS), a summer mesospheric warm bias for SABER (6 K near 60 km), and a vertically structured bias for MLS (−4 to 4 K). We have corrected the satellite data based on the lidar-determined stratopause height and found a significant improvement.
Davide Dionisi, Francesca Barnaba, Henri Diémoz, Luca Di Liberto, and Gian Paolo Gobbi
Atmos. Meas. Tech., 11, 6013–6042, https://doi.org/10.5194/amt-11-6013-2018, https://doi.org/10.5194/amt-11-6013-2018, 2018
Robin Wing, Alain Hauchecorne, Philippe Keckhut, Sophie Godin-Beekmann, Sergey Khaykin, Emily M. McCullough, Jean-François Mariscal, and Éric d'Almeida
Atmos. Meas. Tech., 11, 5531–5547, https://doi.org/10.5194/amt-11-5531-2018, https://doi.org/10.5194/amt-11-5531-2018, 2018
Short summary
Short summary
The objective of this work is to minimize the errors at the highest altitudes of a lidar temperature profile which arise due to background estimation and a priori choice. The systematic method in this paper has the effect of cooling the temperatures at the top of a lidar profile by up to 20 K – bringing them into better agreement with satellite temperatures. Following the description of the algorithm is a 20-year cross-validation of two lidars which establishes the stability of the technique.
Hélène Vérèmes, Guillaume Payen, Philippe Keckhut, Valentin Duflot, Jean-Luc Baray, Jean-Pierre Cammas, Jimmy Leclair De Bellevue, Stéphanie Evan, Françoise Posny, Franck Gabarrot, Jean-Marc Metzger, Nicolas Marquestaut, Susanne Meier, Holger Vömel, and Ruud Dirksen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-32, https://doi.org/10.5194/amt-2017-32, 2017
Preprint withdrawn
Sergey M. Khaykin, Sophie Godin-Beekmann, Philippe Keckhut, Alain Hauchecorne, Julien Jumelet, Jean-Paul Vernier, Adam Bourassa, Doug A. Degenstein, Landon A. Rieger, Christine Bingen, Filip Vanhellemont, Charles Robert, Matthew DeLand, and Pawan K. Bhartia
Atmos. Chem. Phys., 17, 1829–1845, https://doi.org/10.5194/acp-17-1829-2017, https://doi.org/10.5194/acp-17-1829-2017, 2017
Short summary
Short summary
The article is devoted to the long-term evolution and variability of stratospheric aerosol, which plays an important role in climate change and the ozone layer. We use 22-year long continuous observations using laser radar soundings in southern France and satellite-based observations to distinguish between natural aerosol variability (caused by volcanic eruptions) and human-induced change in aerosol concentration. An influence of growing pollution above Asia on stratospheric aerosol is found.
Francesca Costabile, Stefania Gilardoni, Francesca Barnaba, Antonio Di Ianni, Luca Di Liberto, Davide Dionisi, Maurizio Manigrasso, Marco Paglione, Vanes Poluzzi, Matteo Rinaldi, Maria Cristina Facchini, and Gian Paolo Gobbi
Atmos. Chem. Phys., 17, 313–326, https://doi.org/10.5194/acp-17-313-2017, https://doi.org/10.5194/acp-17-313-2017, 2017
Short summary
Short summary
We investigate the particle size distribution and spectral optical properties of brown carbon (BrC) associated with the formation of secondary aerosol in the ambient atmosphere and relate these properties to major aerosol chemical components. We found that BrC occurs in particles in the droplet mode size range, enriched in ammonium nitrate and poor in black carbon (BC), with a strong dependance on the organic aerosol to BC ratio.
Umberto Rizza, Francesca Barnaba, Mario Marcello Miglietta, Cristina Mangia, Luca Di Liberto, Davide Dionisi, Francesca Costabile, Fabio Grasso, and Gian Paolo Gobbi
Atmos. Chem. Phys., 17, 93–115, https://doi.org/10.5194/acp-17-93-2017, https://doi.org/10.5194/acp-17-93-2017, 2017
Aurélien Chauvigné, Karine Sellegri, Maxime Hervo, Nadège Montoux, Patrick Freville, and Philippe Goloub
Atmos. Meas. Tech., 9, 4569–4585, https://doi.org/10.5194/amt-9-4569-2016, https://doi.org/10.5194/amt-9-4569-2016, 2016
M. Sicard, G. D'Amico, A. Comerón, L. Mona, L. Alados-Arboledas, A. Amodeo, H. Baars, J. M. Baldasano, L. Belegante, I. Binietoglou, J. A. Bravo-Aranda, A. J. Fernández, P. Fréville, D. García-Vizcaíno, A. Giunta, M. J. Granados-Muñoz, J. L. Guerrero-Rascado, D. Hadjimitsis, A. Haefele, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, R. E. Mamouri, I. Mattis, F. Molero, N. Montoux, A. Muñoz, C. Muñoz Porcar, F. Navas-Guzmán, D. Nicolae, A. Nisantzi, N. Papagiannopoulos, A. Papayannis, S. Pereira, J. Preißler, M. Pujadas, V. Rizi, F. Rocadenbosch, K. Sellegri, V. Simeonov, G. Tsaknakis, F. Wagner, and G. Pappalardo
Atmos. Meas. Tech., 8, 4587–4613, https://doi.org/10.5194/amt-8-4587-2015, https://doi.org/10.5194/amt-8-4587-2015, 2015
Short summary
Short summary
In the framework of the ACTRIS summer 2012 measurement campaign (8 June–17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. The paper describes the measurement protocol and discusses the delivery of real-time and near-real-time lidar-derived products.
D. Dionisi, P. Keckhut, Y. Courcoux, A. Hauchecorne, J. Porteneuve, J. L. Baray, J. Leclair de Bellevue, H. Vérèmes, F. Gabarrot, G. Payen, R. Decoupes, and J. P. Cammas
Atmos. Meas. Tech., 8, 1425–1445, https://doi.org/10.5194/amt-8-1425-2015, https://doi.org/10.5194/amt-8-1425-2015, 2015
Y. Wang, K. N. Sartelet, M. Bocquet, P. Chazette, M. Sicard, G. D'Amico, J. F. Léon, L. Alados-Arboledas, A. Amodeo, P. Augustin, J. Bach, L. Belegante, I. Binietoglou, X. Bush, A. Comerón, H. Delbarre, D. García-Vízcaino, J. L. Guerrero-Rascado, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, F. Molero, N. Montoux, A. Muñoz, C. Muñoz, D. Nicolae, A. Papayannis, G. Pappalardo, J. Preissler, V. Rizi, F. Rocadenbosch, K. Sellegri, F. Wagner, and F. Dulac
Atmos. Chem. Phys., 14, 12031–12053, https://doi.org/10.5194/acp-14-12031-2014, https://doi.org/10.5194/acp-14-12031-2014, 2014
V. Noel, H. Chepfer, C. Hoareau, M. Reverdy, and G. Cesana
Atmos. Meas. Tech., 7, 1597–1603, https://doi.org/10.5194/amt-7-1597-2014, https://doi.org/10.5194/amt-7-1597-2014, 2014
F. Chane Ming, C. Ibrahim, C. Barthe, S. Jolivet, P. Keckhut, Y.-A. Liou, and Y. Kuleshov
Atmos. Chem. Phys., 14, 641–658, https://doi.org/10.5194/acp-14-641-2014, https://doi.org/10.5194/acp-14-641-2014, 2014
E. G. Larroza, W. M. Nakaema, R. Bourayou, C. Hoareau, E. Landulfo, and P. Keckhut
Atmos. Meas. Tech., 6, 3197–3210, https://doi.org/10.5194/amt-6-3197-2013, https://doi.org/10.5194/amt-6-3197-2013, 2013
J.-L. Baray, Y. Courcoux, P. Keckhut, T. Portafaix, P. Tulet, J.-P. Cammas, A. Hauchecorne, S. Godin Beekmann, M. De Mazière, C. Hermans, F. Desmet, K. Sellegri, A. Colomb, M. Ramonet, J. Sciare, C. Vuillemin, C. Hoareau, D. Dionisi, V. Duflot, H. Vérèmes, J. Porteneuve, F. Gabarrot, T. Gaudo, J.-M. Metzger, G. Payen, J. Leclair de Bellevue, C. Barthe, F. Posny, P. Ricaud, A. Abchiche, and R. Delmas
Atmos. Meas. Tech., 6, 2865–2877, https://doi.org/10.5194/amt-6-2865-2013, https://doi.org/10.5194/amt-6-2865-2013, 2013
O. Bock, P. Bosser, T. Bourcy, L. David, F. Goutail, C. Hoareau, P. Keckhut, D. Legain, A. Pazmino, J. Pelon, K. Pipis, G. Poujol, A. Sarkissian, C. Thom, G. Tournois, and D. Tzanos
Atmos. Meas. Tech., 6, 2777–2802, https://doi.org/10.5194/amt-6-2777-2013, https://doi.org/10.5194/amt-6-2777-2013, 2013
C. Hoareau, P. Keckhut, V. Noel, H. Chepfer, and J.-L. Baray
Atmos. Chem. Phys., 13, 6951–6963, https://doi.org/10.5194/acp-13-6951-2013, https://doi.org/10.5194/acp-13-6951-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties
ampycloud: an open-source algorithm to determine cloud base heights and sky coverage fractions from ceilometer data
Simulation and detection efficiency analysis for measurements of polar mesospheric clouds using a spaceborne wide-field-of-view ultraviolet imager
The Chalmers Cloud Ice Climatology: retrieval implementation and validation
The algorithm of microphysical-parameter profiles of aerosol and small cloud droplets based on the dual-wavelength lidar data
Bayesian cloud-top phase determination for Meteosat Second Generation
Lidar–radar synergistic method to retrieve ice, supercooled water and mixed-phase cloud properties
Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements
A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Identification of ice-over-water multilayer clouds using multispectral satellite data in an artificial neural network
A new approach to crystal habit retrieval from far-infrared spectral radiance measurements
Severe hail detection with C-band dual-polarisation radars using convolutional neural networks
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Contrail altitude estimation using GOES-16 ABI data and deep learning
The Ice Cloud Imager: retrieval of frozen water column properties
PEAKO and peakTree: Tools for detecting and interpreting peaks in cloud radar Doppler spectra – capabilities and limitations
An advanced spatial co-registration of cloud properties for the atmospheric Sentinel missions: Application to TROPOMI
A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations
Infrared Radiometric Image Classification and Segmentation of Cloud Structure Using Deep-learning Framework for Ground-based Infrared Thermal Camera Observations
Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data
Marine cloud base height retrieval from MODIS cloud properties using machine learning
The EarthCARE mission: science data processing chain overview
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Raman lidar-derived optical and microphysical properties of ice crystals within thin Arctic clouds during PARCS campaign
Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements
Deep convective cloud system size and structure across the global tropics and subtropics
A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images
Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system
Segmentation of polarimetric radar imagery using statistical texture
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Supercooled liquid water cloud classification using lidar backscatter peak properties
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS
Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation
Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product
Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
Across-track extension of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-3D product
Insights into 3D cloud radiative transfer effects for the Orbiting Carbon Observatory
Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 1: Model description and Jacobian calculation
Simulation and sensitivity analysis for cloud and precipitation measurements via spaceborne millimeter-wave radar
Johanna Mayer, Bernhard Mayer, Luca Bugliaro, Ralf Meerkötter, and Christiane Voigt
Atmos. Meas. Tech., 17, 5161–5185, https://doi.org/10.5194/amt-17-5161-2024, https://doi.org/10.5194/amt-17-5161-2024, 2024
Short summary
Short summary
This study uses radiative transfer calculations to characterize the relation of two satellite channel combinations (namely infrared window brightness temperature differences – BTDs – of SEVIRI) to the thermodynamic cloud phase. A sensitivity analysis reveals the complex interplay of cloud parameters and their contribution to the observed phase dependence of BTDs. This knowledge helps to design optimal cloud-phase retrievals and to understand their potential and limitations.
Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Sophie Réthoré, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, Pieter du Preez, and Dirk Furrer
Atmos. Meas. Tech., 17, 4891–4914, https://doi.org/10.5194/amt-17-4891-2024, https://doi.org/10.5194/amt-17-4891-2024, 2024
Short summary
Short summary
ampycloud is a new algorithm developed at MeteoSwiss to characterize the height and sky coverage fraction of cloud layers above aerodromes via ceilometer data. This algorithm was devised as part of a larger effort to fully automate the creation of meteorological aerodrome reports (METARs) at Swiss civil airports. The ampycloud algorithm is implemented as a Python package that is made publicly available to the community under the 3-Clause BSD license.
Ke Ren, Haiyang Gao, Shuqi Niu, Shaoyang Sun, Leilei Kou, Yanqing Xie, Liguo Zhang, and Lingbing Bu
Atmos. Meas. Tech., 17, 4825–4842, https://doi.org/10.5194/amt-17-4825-2024, https://doi.org/10.5194/amt-17-4825-2024, 2024
Short summary
Short summary
Ultraviolet imaging technology has significantly advanced the research and development of polar mesospheric clouds (PMCs). In this study, we proposed the wide-field-of-view ultraviolet imager (WFUI) and built a forward model to evaluate the detection capability and efficiency. The results demonstrate that the WFUI performs well in PMC detection and has high detection efficiency. The relationship between ice water content and detection efficiency follows an exponential function distribution.
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
Atmos. Meas. Tech., 17, 4337–4368, https://doi.org/10.5194/amt-17-4337-2024, https://doi.org/10.5194/amt-17-4337-2024, 2024
Short summary
Short summary
The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limitations of currently available data records of cloud properties. In this work, we address this issue by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
Huige Di, Xinhong Wang, Ning Chen, Jing Guo, Wenhui Xin, Shichun Li, Yan Guo, Qing Yan, Yufeng Wang, and Dengxin Hua
Atmos. Meas. Tech., 17, 4183–4196, https://doi.org/10.5194/amt-17-4183-2024, https://doi.org/10.5194/amt-17-4183-2024, 2024
Short summary
Short summary
This study proposes an inversion method for atmospheric-aerosol or cloud microphysical parameters based on dual-wavelength lidar data. It is suitable for the inversion of uniformly mixed and single-property aerosol layers or small cloud droplets. For aerosol particles, the inversion range that this algorithm can achieve is 0.3–1.7 μm. For cloud droplets, it is 1.0–10 μm. This algorithm can quickly obtain the microphysical parameters of atmospheric particles and has better robustness.
Johanna Mayer, Luca Bugliaro, Bernhard Mayer, Dennis Piontek, and Christiane Voigt
Atmos. Meas. Tech., 17, 4015–4039, https://doi.org/10.5194/amt-17-4015-2024, https://doi.org/10.5194/amt-17-4015-2024, 2024
Short summary
Short summary
ProPS (PRObabilistic cloud top Phase retrieval for SEVIRI) is a method to detect clouds and their thermodynamic phase with a geostationary satellite, distinguishing between clear sky and ice, mixed-phase, supercooled and warm liquid clouds. It uses a Bayesian approach based on the lidar–radar product DARDAR. The method allows studying cloud phases, especially mixed-phase and supercooled clouds, rarely observed from geostationary satellites. This can be used for comparison with climate models.
Clémantyne Aubry, Julien Delanoë, Silke Groß, Florian Ewald, Frédéric Tridon, Olivier Jourdan, and Guillaume Mioche
Atmos. Meas. Tech., 17, 3863–3881, https://doi.org/10.5194/amt-17-3863-2024, https://doi.org/10.5194/amt-17-3863-2024, 2024
Short summary
Short summary
Radar–lidar synergy is used to retrieve ice, supercooled water and mixed-phase cloud properties, making the most of the radar sensitivity to ice crystals and the lidar sensitivity to supercooled droplets. A first analysis of the output of the algorithm run on the satellite data is compared with in situ data during an airborne Arctic field campaign, giving a mean percent error of 49 % for liquid water content and 75 % for ice water content.
Gerald G. Mace
Atmos. Meas. Tech., 17, 3679–3695, https://doi.org/10.5194/amt-17-3679-2024, https://doi.org/10.5194/amt-17-3679-2024, 2024
Short summary
Short summary
The number of cloud droplets per unit volume, Nd, in a cloud is important for understanding aerosol–cloud interaction. In this study, we develop techniques to derive cloud droplet number concentration from lidar measurements combined with other remote sensing measurements such as cloud radar and microwave radiometers. We show that deriving Nd is very uncertain, although a synergistic algorithm seems to produce useful characterizations of Nd and effective particle size.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
Short summary
Short summary
This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Sunny Sun-Mack, Patrick Minnis, Yan Chen, Gang Hong, and William L. Smith Jr.
Atmos. Meas. Tech., 17, 3323–3346, https://doi.org/10.5194/amt-17-3323-2024, https://doi.org/10.5194/amt-17-3323-2024, 2024
Short summary
Short summary
Multilayer clouds (MCs) affect the radiation budget differently than single-layer clouds (SCs) and need to be identified in satellite images. A neural network was trained to identify MCs by matching imagery with lidar/radar data. This method correctly identifies ~87 % SCs and MCs with a net accuracy gain of 7.5 % over snow-free surfaces. It is more accurate than most available methods and constitutes a first step in providing a reasonable 3-D characterization of the cloudy atmosphere.
Gianluca Di Natale, Marco Ridolfi, and Luca Palchetti
Atmos. Meas. Tech., 17, 3171–3186, https://doi.org/10.5194/amt-17-3171-2024, https://doi.org/10.5194/amt-17-3171-2024, 2024
Short summary
Short summary
This work aims to define a new approach to retrieve the distribution of the main ice crystal shapes occurring inside ice and cirrus clouds from infrared spectral measurements. The capability of retrieving these shapes of the ice crystals from satellites will allow us to extend the currently available climatologies to be used as physical constraints in general circulation models. This could could allow us to improve their accuracy and prediction performance.
Vincent Forcadell, Clotilde Augros, Olivier Caumont, Kévin Dedieu, Maxandre Ouradou, Cloe David, Jordi Figueras i Ventura, Olivier Laurantin, and Hassan Al-Sakka
EGUsphere, https://doi.org/10.5194/egusphere-2024-1336, https://doi.org/10.5194/egusphere-2024-1336, 2024
Short summary
Short summary
This study demonstrates the potential for enhancing severe hail detection through the application of convolutional neural networks (CNNs) to dual-polarization radar data. It is shown that current methods can be calibrated to significantly enhance their performance for severe hail detection. This study establishes the foundation for the solution of a more complex problem: the estimation of the maximum size of hailstones on the ground using deep learning applied to radar data.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 17, 3011–3028, https://doi.org/10.5194/amt-17-3011-2024, https://doi.org/10.5194/amt-17-3011-2024, 2024
Short summary
Short summary
We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on the multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals always decreases with the increasing distance from the cloud far edge. The decrease is the direct consequence of the fact that the forward peak of particle phase functions is much larger than the receiver field of view.
Vincent R. Meijer, Sebastian D. Eastham, Ian A. Waitz, and Steven R.H. Barrett
EGUsphere, https://doi.org/10.5194/egusphere-2024-961, https://doi.org/10.5194/egusphere-2024-961, 2024
Short summary
Short summary
Aviation's climate impact is partly due to contrails: the clouds that form behind aircraft and which can linger for hours under certain atmospheric conditions. Accurately forecasting these conditions could allow aircraft to avoid forming these contrails and thus reduce their environmental footprint. Our research uses deep learning to identify three-dimensional contrail locations in two-dimensional satellite imagery, which can be used to assess and improve these forecasts.
Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson
EGUsphere, https://doi.org/10.5194/egusphere-2024-829, https://doi.org/10.5194/egusphere-2024-829, 2024
Short summary
Short summary
The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.
Teresa Vogl, Martin Radenz, Fabiola Ramelli, Rosa Gierens, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2024-837, https://doi.org/10.5194/egusphere-2024-837, 2024
Short summary
Short summary
In this study, we present a toolkit of two Python algorithms to extract information about the cloud and precipitation particles present in clouds from data measured by ground-based radar instruments. The data consist of Doppler spectra, in which several peaks are formed by hydrometeor populations with different fall velocities. The detection of the specific peaks makes it possible to assign them to certain particle types, such as small cloud droplets or fast-falling ice particles like graupel.
Athina Argyrouli, Diego Loyola, Fabian Romahn, Ronny Lutz, Víctor Molina García, Pascal Hedelt, Klaus-Peter Heue, and Richard Siddans
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-28, https://doi.org/10.5194/amt-2024-28, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This manuscript describes a new treatment of the spatial mis-registration of cloud properties for Sentinel-5 Precursor, when the footprints of different spectral bands are not perfectly aligned. The methodology exploits synergies between spectrometers and imagers, like TROPOMI and VIIRS. The largest improvements have been identified for heterogeneous scenes at cloud edges. This approach is generic and can also be applied to future Sentinel-4 and Sentinel-5 instruments.
Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, and Matthias Tesche
Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, https://doi.org/10.5194/amt-17-1739-2024, 2024
Short summary
Short summary
We present a novel method for studying aerosol–cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to 1 year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Kélian Sommer, Wassim Kabalan, and Romain Brunet
EGUsphere, https://doi.org/10.5194/egusphere-2024-101, https://doi.org/10.5194/egusphere-2024-101, 2024
Short summary
Short summary
Our research introduces a novel deep-learning approach for classifying and segmenting ground-based infrared thermal images, a crucial step in cloud monitoring. Tests on self-captured data showcase its excellent accuracy in distinguishing image types and in structure segmentation. With potential applications in astronomical observations, our work pioneers a robust solution for ground-based sky quality assessment, promising advancements in the photometric observations experiments.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
Short summary
Short summary
In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
Short summary
Short summary
The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
Short summary
Short summary
We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Julien Lenhardt, Johannes Quaas, and Dino Sejdinovic
EGUsphere, https://doi.org/10.5194/egusphere-2024-327, https://doi.org/10.5194/egusphere-2024-327, 2024
Short summary
Short summary
Clouds play a key role in the regulation of the Earth's climate. Aspects like the height of their base are of essential interest, but remain difficult to derive from satellite data. In this study, we combine observations from the surface and satellite retrievals of cloud properties to build a robust and accurate method to retrieve the cloud base height.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
Short summary
Short summary
The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
Short summary
Short summary
The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
Short summary
Short summary
The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
Short summary
Short summary
The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
Short summary
Short summary
Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
Short summary
Short summary
A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
Short summary
Short summary
Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
Short summary
Short summary
The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
Short summary
Short summary
We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
Short summary
Short summary
Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
Short summary
Short summary
We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
Short summary
Short summary
We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
Short summary
Short summary
The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
Short summary
Short summary
We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Luke Edgar Whitehead, Adrian James McDonald, and Adrien Guyot
EGUsphere, https://doi.org/10.5194/egusphere-2023-1085, https://doi.org/10.5194/egusphere-2023-1085, 2023
Short summary
Short summary
Supercooled liquid water cloud is important to represent in weather and climate models, particularly in the Southern Hemisphere. Previous work has developed a new machine learning method for measuring supercooled liquid water in Antarctic clouds using simple lidar observations. We evaluate this technique using a lidar dataset from Christchurch, New Zealand, and develop an updated algorithm for accurate supercooled liquid water detection at mid-latitudes.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
Short summary
Short summary
The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
Short summary
Short summary
JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
Short summary
Short summary
This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
Atmos. Meas. Tech., 16, 3221–3243, https://doi.org/10.5194/amt-16-3221-2023, https://doi.org/10.5194/amt-16-3221-2023, 2023
Short summary
Short summary
The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
Short summary
Short summary
The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
Short summary
Short summary
We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
Anja Hünerbein, Sebastian Bley, Stefan Horn, Hartwig Deneke, and Andi Walther
Atmos. Meas. Tech., 16, 2821–2836, https://doi.org/10.5194/amt-16-2821-2023, https://doi.org/10.5194/amt-16-2821-2023, 2023
Short summary
Short summary
The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information needed for describing the cloud and aerosol properties in the cross-track direction, complementing the measurements from the Cloud Profiling Radar, Atmospheric Lidar and Broad-Band Radiometer. The accurate discrimination between clear and cloudy pixels is an essential first step. Therefore, the cloud mask algorithm provides a cloud flag, cloud phase and cloud type product for the MSI observations.
Zhipeng Qu, Howard W. Barker, Jason N. S. Cole, and Mark W. Shephard
Atmos. Meas. Tech., 16, 2319–2331, https://doi.org/10.5194/amt-16-2319-2023, https://doi.org/10.5194/amt-16-2319-2023, 2023
Short summary
Short summary
This paper describes EarthCARE’s L2 product ACM-3D. It includes the scene construction algorithm (SCA) used to produce the indexes for reconstructing 3D atmospheric scene based on satellite nadir retrievals. It also provides the information about the buffer zone sizes of 3D assessment domains and the ranking scores for selecting the best 3D assessment domains. These output variables are needed to run 3D radiative transfer models for the radiative closure assessment of EarthCARE’s L2 retrievals.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Sebastian Schmidt, and Steffen Mauceri
Atmos. Meas. Tech., 16, 2145–2166, https://doi.org/10.5194/amt-16-2145-2023, https://doi.org/10.5194/amt-16-2145-2023, 2023
Short summary
Short summary
This paper provides insights into the effects of clouds on Orbiting Carbon Observatory (OCO-2) measurements of CO2. Calculations are carried out that indicate the extent to which this satellite experiment underestimates CO2, due to these cloud effects, as a function of the distance between the surface observation footprint and the nearest cloud. The paper discusses how to lessen the influence of these cloud effects.
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, https://doi.org/10.5194/amt-16-2089-2023, 2023
Short summary
Short summary
We present an evaluation of current retrieval techniques in the ice phase applied to polarimetric radar measurements with collocated in situ observations of aircraft conducted over the Olympic Mountains, Washington State, during winter 2015. Radar estimates of ice properties agreed most with aircraft observations in regions with pronounced radar signatures, but uncertainties were identified that indicate issues of some retrievals, particularly in warmer temperature regimes.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 1803–1847, https://doi.org/10.5194/amt-16-1803-2023, https://doi.org/10.5194/amt-16-1803-2023, 2023
Short summary
Short summary
We describe a new method for measuring the 3D spatial variations in water within clouds using the reflected light of the Sun viewed at multiple different angles by satellites. This is a great improvement over older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Leilei Kou, Zhengjian Lin, Haiyang Gao, Shujun Liao, and Piman Ding
Atmos. Meas. Tech., 16, 1723–1744, https://doi.org/10.5194/amt-16-1723-2023, https://doi.org/10.5194/amt-16-1723-2023, 2023
Short summary
Short summary
Forward modeling of spaceborne millimeter-wave radar composed of eight submodules is presented. We quantify the uncertainties in radar reflectivity that may be caused by the physical model parameters via a sensitivity analysis. The simulations with improved and conventional settings are compared with CloudSat data, and the simulation results are evaluated and analyzed. The results are instructive to the optimization of forward modeling and microphysical parameter retrieval.
Cited articles
Ansmann, A., Wandinger, U., Riebesell, M., Weitkamp, C., and Michaelis, W.: Independent measurement of extinction and backscatter profiles in cirrus clouds by using a combined Raman elastic-backscatter lidar, Appl. Optics, 31, 7113–7113, 1992.
Boehm, M. T., Verlinde, J., and Ackerman, T. P.: On the maintenance of high tropical cirrus, J. Geophys. Res., 104, 24423–24434, 1999.
Cadet, B., Giraud, V., Haeffelin, M., Keckhut, P., Rechou, A., and Baldy, S.: Improved retrievals of the optical properties of cirrus clouds by a combination of lidar methods, Appl. Optics, 44, 1726–1734, 2005.
Chen, W. N., Chiang, C. W., and Nee, J. W.: Lidar Ratio and Depolarization Ratio for Cirrus Clouds, Appl. Optics, 41, 6470–6476, 2002.
Chepfer, H., Bony, S., Winker, D. M., Chiriaco, M., Dufresne, J.-L., and Seze, G.: Use of CALIPSO lidar observations to evaluate the cloudiness simulated by a climate model, Geophys. Res. Lett., 35, L15704, https://doi.org/10.1029/2008GL034207, 2008.
Comstock, J. M., Ackerman, T. P., and Mace, G. G.: Ground-based lidar and radar remote sensing of tropical cirrus clouds at Nauru Island: Cloud statistics and radiative impacts, J. Geophys. Res., 107, 4714, https://doi.org/10.1029/2002JD002203, 2002.
Congeduti, F., Marenco, F., Baldetti, P., and Vincenti, E.: The multiple-mirror lidar "9-eyes", J. Opt. A-Pure Appl. Op., 1, 185–191, 1999.
Davis, S., Hlavka, D., Jensen, E., Rosenlof, K., Yang, Q., Schmidt, S., Borrmann, S., Frey, W., Lawson, P., Voemel, H., and Bui, T. P.: In situ and lidar observations of tropopause subvisible cirrus clouds during TC4, J. Geophys. Res., 115, D00J17, https://doi.org/10.1029/2009JD013093, 2010.
Deng, M. and Mace, G.: Cirrus microphysical properties and air motion statistics using cloud radar Doppler moments. Part I: Algorithm description, J. Appl. Meteor. Clim., 45, 1690–1709, 2006.
Dinh, T. P., Durran, D. R., and Ackerman, T.: The maintenance of tropical tropopause layer cirrus, J. Geophys. Res., 115, D02104, https://doi.org/10.1029/2009JD012735, 2010.
Dionisi, D., Congeduti, F., Liberti, G. L., and Cardillo, F.: Calibration of a Multichannel Water Vapor Raman Lidar through Noncollocated Operational Soundings: Optimization and Characterization of Accuracy and Variability, J. Atmos. Ocean. Tech., 27, 108–121, 2010.
Donovan, D. P. and van Lammeren, A. C. A. P.: Cloud effective particle size and water content profile retrievals using combined lidar and radar observations. Part 1: Theory and simulations, J. Geophys. Res., 106, 27425–27448, 2001.
Draxler, R. R. and Rolph, G. D.: HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) Model, NOAA ARL READY, NOAA Air Resources Laboratory, Silver Spring, MD, available at: http://ready.arl.noaa.gov/HYSPLIT.php (last access: 20 July 2012), 2003.
Dupont, J. C., Haeffelin, M., Morille, Y., Noël, V., Keckhut, P., Winker, D., Comstock, J., Chervet, P., and Roblin, A.: Macrophysical and optical properties of midlatitude cirrus clouds from four ground-based lidars and collocated CALIOP observations, J. Geophys. Res., 115, D00H24, https://doi.org/10.1029/2009JD011943, 2010.
Ferrare, R. A., Turner, D. D., Heilman Brasseur, L., Feltz, W. F., Dubovick, O., and Tooman, T. P.: Raman lidar measurements of the aerosol extinction-to-backscatter ratio over the Southern Great Plains, J. Geophys. Res., 106, 20333–20347, 2001.
Gierens, K., Kohlhepp, R., Dotzek, N., and Smit, H. G.: Instantaneous ?uctuations of temperature and moisture in the upper troposphere and tropopause region. Part 1: Probability densities and their variability, Meteorol. Z., 16, 221–231, 2007.
Goldfarb, L., Keckhut, P., Chanin, M. L., and Hauchecorne, A.: Cirrus climatological results from lidar measurements at OHP, Geophys. Res. Lett., 28, 1687–1690, 2001.
Grund, C. J., Banta, R. M., George, J. L., Howell, J. N., Post, M. J., Richter, R. A., and Weickmann, A. M.: High-resolution Doppler lidar for boundary layer and cloud research, J. Atmos. Ocean. Tech., 18, 376–393, 2001.
Gu, Y., Liou, K. N., Ou, S. C., and Fovell, R.: Cirrus clouds simulations using WRF with improved radiation parameterization and increased vertical resolution, J. Geophys. Res., 116, D06119, https://doi.org/10.1029/2010JD014574, 2011.
Haag, W. and Kärcher, B.: The impact of aerosols and gravity waves on cirrus clouds at midlatitudes, J. Geophys. Res., 109, D12202, https://doi.org/10.1029/2004JD004579, 2004.
Hoareau, C., Keckhut, P., Sarkissian, A., Baray, J. L., and Durry, G.: Methodology for water monitoring in the upper troposphere with Raman lidar at Haute-Provence Observatory, J. Atmos. Ocean. Tech., 26, 2149–2160, 2009.
Immler, F., Treffeisen, R., Engelbart, D., Krüger, K., and Schrems, O.: Cirrus, contrails, and ice supersaturated regions in high pressure systems at northern mid latitudes, Atmos. Chem. Phys., 8, 1689–1699, https://doi.org/10.5194/acp-8-1689-2008, 2008.
Jakob, C.: Ice clouds in numerical weather prediction models, edited by: Lynch, D. K., Sassen, K., Starr, D. O'C., and Stephens, G., Cirrus, Oxford University Press, 327–345, 2002.
Jensen, E., Toon, O., Selkirk, H., Spinhirne, J., and Schoeberl, M.: On the formation and persistence of subvisible cirrus clouds near the tropical tropopause, J. Geophys. Res., 101, 21361–21375, 1996.
Jensen, E. J., Smith, J. B., Pfister, L., Pittman, J. V., Weinstock, E. M., Sayres, D. S., Herman, R. L., Troy, R. F., Rosenlof, K., Thompson, T. L., Fridlind, A. M., Hudson, P. K., Cziczo, D. J., Heymsfield, A. J., Schmitt, C., and Wilson, J. C.: Ice supersaturations exceeding 100 % at the cold tropical tropopause: implications for cirrus formation and dehydration, Atmos. Chem. Phys., 5, 851–862, https://doi.org/10.5194/acp-5-851-2005, 2005.
Jumelet, J., Bekki, S., David, C., and Keckhut, P.: Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements, Atmos. Chem. Phys., 8, 5435-5448, https://doi.org/10.5194/acp-8-5435-2008, 2008.
Kärcher, B.: Supersaturation Fluctuations in Cirrus Clouds Driven by Colored Noise, J. Atmos. Sci., 69, 435–443, 2012.
Keckhut, P., Hauchecorne, A., Bekki, S., Colette, A., David, C., and Jumelet, J.: Indications of thin cirrus clouds in the stratosphere at mid-latitudes, Atmos. Chem. Phys., 5, 3407–3414, https://doi.org/10.5194/acp-5-3407-2005, 2005.
Keckhut, P., Borchi, F., Bekki, S., Hauchecorne, A., and SiLaouina, M.: Cirrus classification at mid-latitude from systematic lidar observations, J. Appl. Meteor. Clim., 45, 249–258, 2006.
Keckhut, P., Perrin, J. M., Thuillier, G., Hoareau, C., Porteneuve, J. P., and Montoux, N.: Subgrid-scale cirrus observed by lidar at mid-latitude: variability of the cloud optical depth, J. Appl. Remote Sens., submitted, 2013.
Khvorostyanov, V. I. and Sassen, K.: Microphysical processes in cirrus and their impact on radiation: a mesoscale modeling perspective, edited by: Lynch, D. K., Sassen, K., Starr, D. O'C., and Stephens, G., Cirrus, Oxford University Press, 397–432, 2002.
Lanzante, J. R.: Resistant, Robust and non-parametric techniques for the analysis of climate data: theory and examples, including applications to historical radiosonde station data, Int. J. Climatol., 16, 1197–1226, 1996.
Lehmann, R., von der Gathen, P., Rex, M., and Streibel, M.: Statistical analysis of the precision of the Match method, Atmos. Chem. Phys., 5, 2713–2727, https://doi.org/10.5194/acp-5-2713-2005, 2005.
Luo, Z. and Rossow, W. B.: Characterizing Tropical Cirrus Life Cycle, Evolution, and Interaction with Upper-Tropospheric Water Vapor Using Lagrangian Trajectory Analysis of Satellite Observations, J. Climate, 17, 4541–4563, 2004.
Montoux, N., Keckhut, P., Hauchecorne, A., Jumelet, J., Brogniez, H., and David, C.: Isentropic modeling of a cirrus cloud event observed in the midlatitude upper troposphere and lower stratosphere, J. Geophys. Res., 115, D02202, https://doi.org/10.1029/2009JD011981, 2010.
Orr, B. W. and Kropfli, R. A.: A Method for Estimating Particle Fall Velocities from Vertically Pointing Doppler Radar, J. Atmos. Ocean. Tech., 16, 29–37, 1999.
Platt, C. M. R. and Dilley, A. C.: Determination of the cirrus particle single-scattering phase function from lidar and solar radiometric data, Appl. Optics, 23, 380–386, 1984.
Rex, M., von der Gathen, P., Harris, N. R. P., Lucic, D., Knudsen, B. M., Braathen, G. O., Reid, S. J., De Backer, H., Claude, H., Fabian, R., Fast, H., Gil, M., Kyrö, E., Mikkelsen, I. S., Rummukainen, M., Smit, H. G., Stähelin, J., Varotsos, C., and Zaitcev, I.: In situ measurements of stratospheric ozone depletion rates in the Arctic winter 1991/1992: A Lagrangian approach, J. Geophys. Res., 103, 5843–5853, 1998.
Rex, M., von der Gathen, P., Braathen, G. O., Harris, N. R. P., Reimer, E., Beck, A., Alfier, R., Krüger-carstensen, R., Chipperfield, M., De Backer, H., Balis, D., O'Connor, F., Dier, H., Dorokhov, V., Fast, H., Gamma, A., Gil, M., Kyrö, E., Litynska, I., Mikkelsen, I. S., Molineux, M., Murphy, G., Reid, S. J., Rummukainen, M., and Zerefos, C.: Chemical ozone loss in the Arctic winter 1994/95 as determined by the Match technique, J. Atmos. Chem., 32, 35–59, 1999.
Sanderson, B. M., Piani, C., and Ingram, W. J.: Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations, Clim. Dynam., 30, 175–190, https://doi.org/10.1007/s00382-007-0280-7, 2008.
Sassen, K. and Campbell, J. R.: A midlatitude cirrus cloud climatology from the facility for atmospheric remote sensing. Part1: Macrophysical and synoptic properties, J. Atmos. Sci., 58, 481–496, 2001.
Sassen, K., Wang, Z., and Liu, D.: Global distribution of cirrus clouds from CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements, J. Geophys. Res., 113, D00A12, https://doi.org/10.1029/2008JD009972, 2008.
Sassen, K., Wang, Z., and Liu, D.: Cirrus clouds and deep convection in the tropics: Insights from CALIPSO and CloudSat, J. Geophys. Res., 114, D00H06, https://doi.org/10.1029/2009JD011916, 2009.
Schmitt, C. G. and Heymsfield, A. J.: The Size Distribution and Mass-Weighted Terminal Velocity of Low-Latitude Tropopause Cirrus Crystal Populations, J. Atmos. Sci., 66, 2013–2028, 2009.
Sherlock, V. J., Garnier, A., Hauchecorne, A., and Keckhut, P.: Implementation and validation of a Raman backscatter lidar measurement of mid and upper tropospheric water vapour, Appl. Optics, 38, 5838–5850, 1999.
Spichtinger, P. and Gierens, K. M.: Modelling of cirrus clouds – Part 1b: Structuring cirrus clouds by dynamics, Atmos. Chem. Phys., 9, 707–719, https://doi.org/10.5194/acp-9-707-2009, 2009.
Stubenrauch, C., Rossow, W., Scott, N., and Chedin, A.: Clouds as seen by satellite sounders (3I) and imagers (ISCCP). Part III: Spatial heterogeneity and radiative effects, J. Climate, 12, 3419–3442, 1999.
Taylor, J. R., Randel, W. J., and Jensen, E. J.: Cirrus cloud-temperature interactions in the tropical tropopause layer: a case study, Atmos. Chem. Phys., 11, 10085–10095, https://doi.org/10.5194/acp-11-10085-2011, 2011.
Tinel, C., Testud, J., Pelon, J., Hogan, R., Protat, A., Delanoë, J., and Bouniol, D.: The retrieval of ice cloud properties from cloud radar and lidar synergy, J. Appl. Meteorol., 44, 860–875, 2005.
Von der Gathen, P., Rex, M., Harris, N. R. P., Lucic, D., Knudsen, B. M., Braathen, G. O., De Backer, H., Fabian, R., Fast, H., Gil, M., Kyrö, E., Mikkelsen, I. S., Rummukainen, M., Stähelin, J., and Varotsos, C.: Observational evidence for chemical ozone depletion over the Arctic in winter 1991–92, Nature, 375, 131–134, 1995.
