Articles | Volume 12, issue 2
https://doi.org/10.5194/gi-12-171-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gi-12-171-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Collaborative development of the Lidar Processing Pipeline (LPP) for retrievals of atmospheric aerosols and clouds
Juan Vicente Pallotta
CORRESPONDING AUTHOR
Centro de Investigaciones en Láseres y Aplicaciones, UNIDEF (CITEDEF-CONICET), Buenos Aires, Argentina
Silvânia Alves de Carvalho
Department of Exact Sciences, Volta Redonda School of Industrial Metallurgical Engineering, Fluminense Federal University, Av. dos Trabalhadores 420, 27255-125, Volta Redonda, RJ, Brazil
Fabio Juliano da Silva Lopes
Centro de Lasers e Aplicações (CELAP), Instituto de Pesquisas Energéticas e Nucleares (IPEN), Av. Prof. Lineu Prestes 2242, 05508-000, São Paulo, SP, Brazi
Alexandre Cacheffo
Institute of Exact and Natural Sciences of Pontal (ICENP), Federal University of Uberlândia (UFU), Campus Pontal. Rua Vinte, 1600, Bloco C, 38304-402, Ituiutaba, MG, Brazil
Eduardo Landulfo
Centro de Lasers e Aplicações (CELAP), Instituto de Pesquisas Energéticas e Nucleares (IPEN), Av. Prof. Lineu Prestes 2242, 05508-000, São Paulo, SP, Brazi
Henrique Melo Jorge Barbosa
Department of Physics, University of Maryland Baltimore County, Baltimore, MD 21250, USA
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Nelson Bègue, Lerato Shikwambana, Hassan Bencherif, Juan Pallotta, Venkataraman Sivakumar, Elian Wolfram, Nkanyiso Mbatha, Facundo Orte, David Jean Du Preez, Marion Ranaivombola, Stuart Piketh, and Paola Formenti
Ann. Geophys., 38, 395–420, https://doi.org/10.5194/angeo-38-395-2020, https://doi.org/10.5194/angeo-38-395-2020, 2020
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This study investigates the influence of the 2015 Calbuco eruption (41.2°S, 72.4°W; Chile) on the total columnar aerosol optical properties in the Southern Hemisphere. The well-known technique of sun photometry was applied to the investigation of the transport and the spatio-temporal evolution of the optical properties of the volcanic plume. The CIMEL sun photometer measurements performed over six South American and three African sites were statistically analyzed.
Brent A. McBride, J. Vanderlei Martins, J. Dominik Cieslak, Roberto Fernandez-Borda, Anin Puthukkudy, Xiaoguang Xu, Noah Sienkiewicz, Brian Cairns, and Henrique M. J. Barbosa
Atmos. Meas. Tech., 17, 5709–5729, https://doi.org/10.5194/amt-17-5709-2024, https://doi.org/10.5194/amt-17-5709-2024, 2024
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The Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) is a new Earth-observing instrument that provides highly accurate measurements of the atmosphere and surface. Using a physics-based calibration technique, we show that AirHARP achieves high measurement accuracy in laboratory and field environments and exceeds a benchmark accuracy requirement for modern aerosol and cloud climate observations. Therefore, the HARP design is highly attractive for upcoming NASA climate missions.
Leandro Alex Moreira Viscardi, Giuseppe Torri, David K. Adams, and Henrique de Melo Jorge Barbosa
Atmos. Chem. Phys., 24, 8529–8548, https://doi.org/10.5194/acp-24-8529-2024, https://doi.org/10.5194/acp-24-8529-2024, 2024
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We evaluate the environmental conditions that control how clouds grow from fair weather cumulus into severe thunderstorms during the Amazonian wet season. Days with rain clouds begin with more moisture in the air and have strong convergence in the afternoon, while precipitation intensity increases with large-scale vertical velocity, moisture, and low-level wind. These results contribute to understanding how clouds form over the rainforest.
Cássia Maria Leme Beu and Eduardo Landulfo
Wind Energ. Sci., 9, 1431–1450, https://doi.org/10.5194/wes-9-1431-2024, https://doi.org/10.5194/wes-9-1431-2024, 2024
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Extrapolating the wind profile for complex terrain through the long short-term memory model outperformed the traditional power law methodology, which due to its universal nature cannot capture local features as the machine-learning methodology does. Moreover, considering the importance of investigating the wind potential and the need for alternative energy sources, it is motivating to find that a short observational campaign can produce better results than the traditional techniques.
Elion Daniel Hack, Theotonio Pauliquevis, Henrique Melo Jorge Barbosa, Marcia Akemi Yamasoe, Dimitri Klebe, and Alexandre Lima Correia
Atmos. Meas. Tech., 16, 1263–1278, https://doi.org/10.5194/amt-16-1263-2023, https://doi.org/10.5194/amt-16-1263-2023, 2023
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Water vapor is a key factor when seeking to understand fast-changing processes when clouds and storms form and develop. We show here how images from a calibrated infrared camera can be used to derive how much water vapor there is in the atmosphere at a given time. Comparing our results to an established technique, for a case of stable atmospheric conditions, we found an agreement within 2.8 %. Water vapor sky maps can be retrieved every few minutes, day or night, under partly cloudy skies.
Marco A. Franco, Florian Ditas, Leslie A. Kremper, Luiz A. T. Machado, Meinrat O. Andreae, Alessandro Araújo, Henrique M. J. Barbosa, Joel F. de Brito, Samara Carbone, Bruna A. Holanda, Fernando G. Morais, Janaína P. Nascimento, Mira L. Pöhlker, Luciana V. Rizzo, Marta Sá, Jorge Saturno, David Walter, Stefan Wolff, Ulrich Pöschl, Paulo Artaxo, and Christopher Pöhlker
Atmos. Chem. Phys., 22, 3469–3492, https://doi.org/10.5194/acp-22-3469-2022, https://doi.org/10.5194/acp-22-3469-2022, 2022
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In Central Amazonia, new particle formation in the planetary boundary layer is rare. Instead, there is the appearance of sub-50 nm aerosols with diameters larger than about 20 nm that eventually grow to cloud condensation nuclei size range. Here, 254 growth events were characterized which have higher predominance in the wet season. About 70 % of them showed direct relation to convective downdrafts, while 30 % occurred partly under clear-sky conditions, evidencing still unknown particle sources.
Janaína P. Nascimento, Megan M. Bela, Bruno B. Meller, Alessandro L. Banducci, Luciana V. Rizzo, Angel Liduvino Vara-Vela, Henrique M. J. Barbosa, Helber Gomes, Sameh A. A. Rafee, Marco A. Franco, Samara Carbone, Glauber G. Cirino, Rodrigo A. F. Souza, Stuart A. McKeen, and Paulo Artaxo
Atmos. Chem. Phys., 21, 6755–6779, https://doi.org/10.5194/acp-21-6755-2021, https://doi.org/10.5194/acp-21-6755-2021, 2021
Anin Puthukkudy, J. Vanderlei Martins, Lorraine A. Remer, Xiaoguang Xu, Oleg Dubovik, Pavel Litvinov, Brent McBride, Sharon Burton, and Henrique M. J. Barbosa
Atmos. Meas. Tech., 13, 5207–5236, https://doi.org/10.5194/amt-13-5207-2020, https://doi.org/10.5194/amt-13-5207-2020, 2020
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In this work, we report the demonstration and validation of the aerosol properties retrieved using AirHARP and GRASP for data from the NASA ACEPOL campaign 2017. These results serve as a proxy for the scale and detail of aerosol retrievals that are anticipated from future space mission data, as HARP CubeSat (mission begins 2020) and HARP2 (aboard the NASA PACE mission with the launch in 2023) are near duplicates of AirHARP and are expected to provide the same level of aerosol characterization.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
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The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign is a resource for the next generation of spaceborne multi-angle polarimeter (MAP) and lidar missions. Conducted in the fall of 2017 from the Armstrong Flight Research Center in Palmdale, California, four MAP instruments and two lidars were flown on the high-altitude ER-2 aircraft over a variety of scene types and ground assets. Data are freely available to the public and useful for algorithm development and testing.
Bruna A. Holanda, Mira L. Pöhlker, David Walter, Jorge Saturno, Matthias Sörgel, Jeannine Ditas, Florian Ditas, Christiane Schulz, Marco Aurélio Franco, Qiaoqiao Wang, Tobias Donth, Paulo Artaxo, Henrique M. J. Barbosa, Stephan Borrmann, Ramon Braga, Joel Brito, Yafang Cheng, Maximilian Dollner, Johannes W. Kaiser, Thomas Klimach, Christoph Knote, Ovid O. Krüger, Daniel Fütterer, Jošt V. Lavrič, Nan Ma, Luiz A. T. Machado, Jing Ming, Fernando G. Morais, Hauke Paulsen, Daniel Sauer, Hans Schlager, Johannes Schneider, Hang Su, Bernadett Weinzierl, Adrian Walser, Manfred Wendisch, Helmut Ziereis, Martin Zöger, Ulrich Pöschl, Meinrat O. Andreae, and Christopher Pöhlker
Atmos. Chem. Phys., 20, 4757–4785, https://doi.org/10.5194/acp-20-4757-2020, https://doi.org/10.5194/acp-20-4757-2020, 2020
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Biomass burning smoke from African savanna and grassland is transported across the South Atlantic Ocean in defined layers within the free troposphere. The combination of in situ aircraft and ground-based measurements aided by satellite observations showed that these layers are transported into the Amazon Basin during the early dry season. The influx of aged smoke, enriched in black carbon and cloud condensation nuclei, has important implications for the Amazonian aerosol and cloud cycling.
Brent A. McBride, J. Vanderlei Martins, Henrique M. J. Barbosa, William Birmingham, and Lorraine A. Remer
Atmos. Meas. Tech., 13, 1777–1796, https://doi.org/10.5194/amt-13-1777-2020, https://doi.org/10.5194/amt-13-1777-2020, 2020
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Clouds play a large role in the way our Earth system distributes energy. The measurement of cloud droplet size distribution (DSD) is one way to connect small-scale cloud processes to scattered radiation. Our small satellite instrument, the Airborne Hyper-Angular Rainbow Polarimeter, is the first to infer DSDs over a wide spatial cloud field using polarized light. This study improves the way we interpret cloud properties and shows that high-quality science does not require a large taxpayer cost.
Nelson Bègue, Lerato Shikwambana, Hassan Bencherif, Juan Pallotta, Venkataraman Sivakumar, Elian Wolfram, Nkanyiso Mbatha, Facundo Orte, David Jean Du Preez, Marion Ranaivombola, Stuart Piketh, and Paola Formenti
Ann. Geophys., 38, 395–420, https://doi.org/10.5194/angeo-38-395-2020, https://doi.org/10.5194/angeo-38-395-2020, 2020
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This study investigates the influence of the 2015 Calbuco eruption (41.2°S, 72.4°W; Chile) on the total columnar aerosol optical properties in the Southern Hemisphere. The well-known technique of sun photometry was applied to the investigation of the transport and the spatio-temporal evolution of the optical properties of the volcanic plume. The CIMEL sun photometer measurements performed over six South American and three African sites were statistically analyzed.
Gregori de Arruda Moreira, Fábio Juliano da Silva Lopes, Juan Luis Guerrero-Rascado, Jonatan João da Silva, Antonio Arleques Gomes, Eduardo Landulfo, and Lucas Alados-Arboledas
Atmos. Meas. Tech., 12, 4261–4276, https://doi.org/10.5194/amt-12-4261-2019, https://doi.org/10.5194/amt-12-4261-2019, 2019
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In this paper, we present a comparative analysis of the use of lidar-backscattered signals at three wavelengths (355, 532 and 1064 nm) to study the ABL by investigating high-order moments, which gives us information about the ABL height (derived using the variance method), aerosol layer movements (skewness) and mixing conditions (kurtosis) at several heights.
Suzane S. de Sá, Luciana V. Rizzo, Brett B. Palm, Pedro Campuzano-Jost, Douglas A. Day, Lindsay D. Yee, Rebecca Wernis, Gabriel Isaacman-VanWertz, Joel Brito, Samara Carbone, Yingjun J. Liu, Arthur Sedlacek, Stephen Springston, Allen H. Goldstein, Henrique M. J. Barbosa, M. Lizabeth Alexander, Paulo Artaxo, Jose L. Jimenez, and Scot T. Martin
Atmos. Chem. Phys., 19, 7973–8001, https://doi.org/10.5194/acp-19-7973-2019, https://doi.org/10.5194/acp-19-7973-2019, 2019
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This study investigates the impacts of urban and fire emissions on the concentration, composition, and optical properties of submicron particulate matter (PM1) in central Amazonia during the dry season. Biomass-burning and urban emissions appeared to contribute at least 80 % of brown carbon absorption while accounting for 30 % to 40 % of the organic PM1 mass concentration. Only a fraction of the 9-fold increase in mass concentration relative to the wet season was due to biomass burning.
Nilton E. Rosário, Thamara Sauini, Theotonio Pauliquevis, Henrique M. J. Barbosa, Marcia A. Yamasoe, and Boris Barja
Atmos. Meas. Tech., 12, 921–934, https://doi.org/10.5194/amt-12-921-2019, https://doi.org/10.5194/amt-12-921-2019, 2019
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Does pristine Amazonian forest atmosphere provide successful calibration of a Sun photometer based on the Langley plot method? This question emerged from the challenge of maintaining regular calibration of a Sun photometer dedicated to long-term monitoring of aerosol optical properties in Amazonia, far from clean mountaintops. Our results show that on-site calibrated Sun photometers, under pristine Amazonian conditions, are able to provide consistent retrieval of aerosol optical depth.
Gregori de Arruda Moreira, Juan Luis Guerrero-Rascado, Jose A. Benavent-Oltra, Pablo Ortiz-Amezcua, Roberto Román, Andrés E. Bedoya-Velásquez, Juan Antonio Bravo-Aranda, Francisco Jose Olmo Reyes, Eduardo Landulfo, and Lucas Alados-Arboledas
Atmos. Chem. Phys., 19, 1263–1280, https://doi.org/10.5194/acp-19-1263-2019, https://doi.org/10.5194/acp-19-1263-2019, 2019
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In this study we show the capabilities of combining different remote sensing systems (microwave radiometer – MWR, Doppler lidar – DL – and elastic lidar – EL) for retrieving a detailed picture of the PBL turbulent features. Concerning EL, in addition to analyzing the influence of noise, we explore the use of different wavelengths, which usually includes EL systems operated in extended networks, like EARLINET, LALINET, MPLNET or SKYNET.
Igor Veselovskii, Philippe Goloub, Qiaoyun Hu, Thierry Podvin, David N. Whiteman, Mikhael Korenskiy, and Eduardo Landulfo
Atmos. Meas. Tech., 12, 119–128, https://doi.org/10.5194/amt-12-119-2019, https://doi.org/10.5194/amt-12-119-2019, 2019
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Methane is currently the second most important greenhouse gas of anthropogenic origin (after carbon dioxide) and its concentration can be increased inside the boundary layer. So, the development of instruments for vertical profiling of the methane mixing ratio is an important task. We present the results of methane profiling in the lower troposphere using LILAS Raman lidar from the Lille University observatory platform (France).
Suzane S. de Sá, Brett B. Palm, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Gabriel Isaacman-VanWertz, Lindsay D. Yee, Joel Brito, Samara Carbone, Igor O. Ribeiro, Glauber G. Cirino, Yingjun Liu, Ryan Thalman, Arthur Sedlacek, Aaron Funk, Courtney Schumacher, John E. Shilling, Johannes Schneider, Paulo Artaxo, Allen H. Goldstein, Rodrigo A. F. Souza, Jian Wang, Karena A. McKinney, Henrique Barbosa, M. Lizabeth Alexander, Jose L. Jimenez, and Scot T. Martin
Atmos. Chem. Phys., 18, 12185–12206, https://doi.org/10.5194/acp-18-12185-2018, https://doi.org/10.5194/acp-18-12185-2018, 2018
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This study aimed at understanding and quantifying the changes in mass concentration and composition of submicron airborne particulate matter (PM) in Amazonia due to urban pollution. Downwind of Manaus, PM concentrations increased by up to 200 % under polluted compared with background conditions. The observed changes included contributions from both primary and secondary processes. The differences in organic PM composition suggested a shift in the pathways of secondary production with pollution.
Mira L. Pöhlker, Florian Ditas, Jorge Saturno, Thomas Klimach, Isabella Hrabě de Angelis, Alessandro C. Araùjo, Joel Brito, Samara Carbone, Yafang Cheng, Xuguang Chi, Reiner Ditz, Sachin S. Gunthe, Bruna A. Holanda, Konrad Kandler, Jürgen Kesselmeier, Tobias Könemann, Ovid O. Krüger, Jošt V. Lavrič, Scot T. Martin, Eugene Mikhailov, Daniel Moran-Zuloaga, Luciana V. Rizzo, Diana Rose, Hang Su, Ryan Thalman, David Walter, Jian Wang, Stefan Wolff, Henrique M. J. Barbosa, Paulo Artaxo, Meinrat O. Andreae, Ulrich Pöschl, and Christopher Pöhlker
Atmos. Chem. Phys., 18, 10289–10331, https://doi.org/10.5194/acp-18-10289-2018, https://doi.org/10.5194/acp-18-10289-2018, 2018
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This paper presents the aerosol and cloud condensation nuclei (CCN) variability for characteristic atmospheric states – such as biomass burning, long-range transport, and pristine rain forest conditions – in the vulnerable and climate-relevant Amazon Basin. It summarizes the key properties of aerosol and CCN and, thus, provides a basis for an in-depth analysis of aerosol–cloud interactions in the Amazon region.
Meinrat O. Andreae, Armin Afchine, Rachel Albrecht, Bruna Amorim Holanda, Paulo Artaxo, Henrique M. J. Barbosa, Stephan Borrmann, Micael A. Cecchini, Anja Costa, Maximilian Dollner, Daniel Fütterer, Emma Järvinen, Tina Jurkat, Thomas Klimach, Tobias Konemann, Christoph Knote, Martina Krämer, Trismono Krisna, Luiz A. T. Machado, Stephan Mertes, Andreas Minikin, Christopher Pöhlker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Daniel Sauer, Hans Schlager, Martin Schnaiter, Johannes Schneider, Christiane Schulz, Antonio Spanu, Vinicius B. Sperling, Christiane Voigt, Adrian Walser, Jian Wang, Bernadett Weinzierl, Manfred Wendisch, and Helmut Ziereis
Atmos. Chem. Phys., 18, 921–961, https://doi.org/10.5194/acp-18-921-2018, https://doi.org/10.5194/acp-18-921-2018, 2018
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We made airborne measurements of aerosol particle concentrations and properties over the Amazon Basin. We found extremely high concentrations of very small particles in the region between 8 and 14 km altitude all across the basin, which had been recently formed by gas-to-particle conversion at these altitudes. This makes the upper troposphere a very important source region of atmospheric particles with significant implications for the Earth's climate system.
Ryan Thalman, Suzane S. de Sá, Brett B. Palm, Henrique M. J. Barbosa, Mira L. Pöhlker, M. Lizabeth Alexander, Joel Brito, Samara Carbone, Paulo Castillo, Douglas A. Day, Chongai Kuang, Antonio Manzi, Nga Lee Ng, Arthur J. Sedlacek III, Rodrigo Souza, Stephen Springston, Thomas Watson, Christopher Pöhlker, Ulrich Pöschl, Meinrat O. Andreae, Paulo Artaxo, Jose L. Jimenez, Scot T. Martin, and Jian Wang
Atmos. Chem. Phys., 17, 11779–11801, https://doi.org/10.5194/acp-17-11779-2017, https://doi.org/10.5194/acp-17-11779-2017, 2017
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Particle hygroscopicity, mixing state, and the hygroscopicity of organic components were characterized in central Amazonia for 1 year; their seasonal and diel variations were driven by a combination of primary emissions, photochemical oxidation, and boundary layer development. The relationship between the hygroscopicity of organic components and their oxidation level was examined, and the results help to reconcile the differences among the relationships observed in previous studies.
Micael A. Cecchini, Luiz A. T. Machado, Meinrat O. Andreae, Scot T. Martin, Rachel I. Albrecht, Paulo Artaxo, Henrique M. J. Barbosa, Stephan Borrmann, Daniel Fütterer, Tina Jurkat, Christoph Mahnke, Andreas Minikin, Sergej Molleker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Christiane Voigt, Bernadett Weinzierl, and Manfred Wendisch
Atmos. Chem. Phys., 17, 10037–10050, https://doi.org/10.5194/acp-17-10037-2017, https://doi.org/10.5194/acp-17-10037-2017, 2017
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We study the effects of aerosol particles and updraft speed on the warm phase of Amazonian clouds. We expand the sensitivity analysis usually found in the literature by concomitantly considering cloud evolution and the effects on droplet size distribution (DSD) shape. The quantitative results show that particle concentration is the primary driver for the vertical profiles of effective diameter and droplet concentration in the warm phase of Amazonian convective clouds.
Diego A. Gouveia, Boris Barja, Henrique M. J. Barbosa, Patric Seifert, Holger Baars, Theotonio Pauliquevis, and Paulo Artaxo
Atmos. Chem. Phys., 17, 3619–3636, https://doi.org/10.5194/acp-17-3619-2017, https://doi.org/10.5194/acp-17-3619-2017, 2017
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We derive the first comprehensive statistics of cirrus clouds over a tropical rain forest. Monthly frequency of occurrence can be as high as 88 %. The diurnal cycle follows that of precipitation, and frequently cirrus is found in the tropopause layer. The mean values of cloud top, base, thickness, optical depth and lidar ratio were 14.3 km, 12.9 km, 1.4 km, 0.25, and 23 sr respectively. The high fraction (42 %) of subvisible clouds may contaminate satellite measurements to an unknown extent.
Mira L. Pöhlker, Christopher Pöhlker, Florian Ditas, Thomas Klimach, Isabella Hrabe de Angelis, Alessandro Araújo, Joel Brito, Samara Carbone, Yafang Cheng, Xuguang Chi, Reiner Ditz, Sachin S. Gunthe, Jürgen Kesselmeier, Tobias Könemann, Jošt V. Lavrič, Scot T. Martin, Eugene Mikhailov, Daniel Moran-Zuloaga, Diana Rose, Jorge Saturno, Hang Su, Ryan Thalman, David Walter, Jian Wang, Stefan Wolff, Henrique M. J. Barbosa, Paulo Artaxo, Meinrat O. Andreae, and Ulrich Pöschl
Atmos. Chem. Phys., 16, 15709–15740, https://doi.org/10.5194/acp-16-15709-2016, https://doi.org/10.5194/acp-16-15709-2016, 2016
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The paper presents a systematic characterization of cloud condensation nuclei (CCN) concentration in the central Amazonian atmosphere. Our results show that the CCN population in this globally important ecosystem follows a pollution-related seasonal cycle, in which it mainly depends on changes in total aerosol size distribution and to a minor extent in the aerosol chemical composition. Our results allow an efficient modeling and prediction of the CCN population based on a novel approach.
Carlos Eduardo Souto-Oliveira, Maria de Fátima Andrade, Prashant Kumar, Fábio Juliano da Silva Lopes, Marly Babinski, and Eduardo Landulfo
Atmos. Chem. Phys., 16, 14635–14656, https://doi.org/10.5194/acp-16-14635-2016, https://doi.org/10.5194/acp-16-14635-2016, 2016
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The Metropolitan Area of São Paulo is the biggest megacity of South America, with over 20 million inhabitants. In recent years, the region has been facing a modification in rain patterns. In this study, we evaluated the effects of local and remote sources of air pollution on cloud-condensation nuclei activation properties. Our results showed that the local vehicular traffic emission products presented more negative effects on cloud-condensation nuclei activation than the remote sources.
Francesca Sprovieri, Nicola Pirrone, Mariantonia Bencardino, Francesco D'Amore, Francesco Carbone, Sergio Cinnirella, Valentino Mannarino, Matthew Landis, Ralf Ebinghaus, Andreas Weigelt, Ernst-Günther Brunke, Casper Labuschagne, Lynwill Martin, John Munthe, Ingvar Wängberg, Paulo Artaxo, Fernando Morais, Henrique de Melo Jorge Barbosa, Joel Brito, Warren Cairns, Carlo Barbante, María del Carmen Diéguez, Patricia Elizabeth Garcia, Aurélien Dommergue, Helene Angot, Olivier Magand, Henrik Skov, Milena Horvat, Jože Kotnik, Katie Alana Read, Luis Mendes Neves, Bernd Manfred Gawlik, Fabrizio Sena, Nikolay Mashyanov, Vladimir Obolkin, Dennis Wip, Xin Bin Feng, Hui Zhang, Xuewu Fu, Ramesh Ramachandran, Daniel Cossa, Joël Knoery, Nicolas Marusczak, Michelle Nerentorp, and Claus Norstrom
Atmos. Chem. Phys., 16, 11915–11935, https://doi.org/10.5194/acp-16-11915-2016, https://doi.org/10.5194/acp-16-11915-2016, 2016
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This work presents atmospheric Hg concentrations recorded within the GMOS global network analyzing Hg measurement results in terms of temporal trends, seasonality and comparability within the network. The over-arching benefit of this coordinated Hg monitoring network would clearly be the production of high-quality measurement datasets on a global scale useful in developing and validating models on different spatial and temporal scales.
James D. Whitehead, Eoghan Darbyshire, Joel Brito, Henrique M. J. Barbosa, Ian Crawford, Rafael Stern, Martin W. Gallagher, Paul H. Kaye, James D. Allan, Hugh Coe, Paulo Artaxo, and Gordon McFiggans
Atmos. Chem. Phys., 16, 9727–9743, https://doi.org/10.5194/acp-16-9727-2016, https://doi.org/10.5194/acp-16-9727-2016, 2016
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We present measurements of aerosols during the transition from wet to dry seasons at a pristine rainforest site in central Amazonia. By excluding pollution episodes, we focus on natural biogenic aerosols. Submicron aerosols are dominated by organic material, similar to previous wet season measurements. Larger particles are dominated by biological material, mostly fungal spores, with higher concentrations at night. This study provides important data on the nature of particles above the Amazon.
S. T. Martin, P. Artaxo, L. A. T. Machado, A. O. Manzi, R. A. F. Souza, C. Schumacher, J. Wang, M. O. Andreae, H. M. J. Barbosa, J. Fan, G. Fisch, A. H. Goldstein, A. Guenther, J. L. Jimenez, U. Pöschl, M. A. Silva Dias, J. N. Smith, and M. Wendisch
Atmos. Chem. Phys., 16, 4785–4797, https://doi.org/10.5194/acp-16-4785-2016, https://doi.org/10.5194/acp-16-4785-2016, 2016
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The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment took place in central Amazonia throughout 2014 and 2015. The experiment focused on the complex links among vegetation, atmospheric chemistry, and aerosol production on the one hand and their connections to aerosols, clouds, and precipitation on the other, especially when altered by urban pollution. This article serves as an introduction to the special issue of publications presenting findings of this experiment.
M. O. Andreae, O. C. Acevedo, A. Araùjo, P. Artaxo, C. G. G. Barbosa, H. M. J. Barbosa, J. Brito, S. Carbone, X. Chi, B. B. L. Cintra, N. F. da Silva, N. L. Dias, C. Q. Dias-Júnior, F. Ditas, R. Ditz, A. F. L. Godoi, R. H. M. Godoi, M. Heimann, T. Hoffmann, J. Kesselmeier, T. Könemann, M. L. Krüger, J. V. Lavric, A. O. Manzi, A. P. Lopes, D. L. Martins, E. F. Mikhailov, D. Moran-Zuloaga, B. W. Nelson, A. C. Nölscher, D. Santos Nogueira, M. T. F. Piedade, C. Pöhlker, U. Pöschl, C. A. Quesada, L. V. Rizzo, C.-U. Ro, N. Ruckteschler, L. D. A. Sá, M. de Oliveira Sá, C. B. Sales, R. M. N. dos Santos, J. Saturno, J. Schöngart, M. Sörgel, C. M. de Souza, R. A. F. de Souza, H. Su, N. Targhetta, J. Tóta, I. Trebs, S. Trumbore, A. van Eijck, D. Walter, Z. Wang, B. Weber, J. Williams, J. Winderlich, F. Wittmann, S. Wolff, and A. M. Yáñez-Serrano
Atmos. Chem. Phys., 15, 10723–10776, https://doi.org/10.5194/acp-15-10723-2015, https://doi.org/10.5194/acp-15-10723-2015, 2015
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This paper describes the Amazon Tall Tower Observatory (ATTO), a new atmosphere-biosphere observatory located in the remote Amazon Basin. It presents results from ecosystem ecology, meteorology, trace gas, and aerosol measurements collected at the ATTO site during the first 3 years of operation.
D. C. Zemp, C.-F. Schleussner, H. M. J. Barbosa, R. J. van der Ent, J. F. Donges, J. Heinke, G. Sampaio, and A. Rammig
Atmos. Chem. Phys., 14, 13337–13359, https://doi.org/10.5194/acp-14-13337-2014, https://doi.org/10.5194/acp-14-13337-2014, 2014
H. M. J. Barbosa, B. Barja, T. Pauliquevis, D. A. Gouveia, P. Artaxo, G. G. Cirino, R. M. N. Santos, and A. B. Oliveira
Atmos. Meas. Tech., 7, 1745–1762, https://doi.org/10.5194/amt-7-1745-2014, https://doi.org/10.5194/amt-7-1745-2014, 2014
F. J. S. Lopes, E. Landulfo, and M. A. Vaughan
Atmos. Meas. Tech., 6, 3281–3299, https://doi.org/10.5194/amt-6-3281-2013, https://doi.org/10.5194/amt-6-3281-2013, 2013
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
Related subject area
Lidar
Comparing triple and single Doppler lidar wind measurements with sonic anemometer data based on a new filter strategy for virtual tower measurements
MOLISENS: MObile LIdar SENsor System to exploit the potential of small industrial lidar devices for geoscientific applications
Architecture of solution for panoramic image blurring in GIS project application
Dense point cloud acquisition with a low-cost Velodyne VLP-16
Kevin Wolz, Christopher Holst, Frank Beyrich, Eileen Päschke, and Matthias Mauder
Geosci. Instrum. Method. Data Syst., 13, 205–223, https://doi.org/10.5194/gi-13-205-2024, https://doi.org/10.5194/gi-13-205-2024, 2024
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We compared wind measurements using different lidar setups at various heights. The triple Doppler lidar, sonic anemometer, and two single Doppler lidars were tested. Overall, the lidar methods showed good agreement with the sonic anemometer. The triple Doppler lidar performed better than single Doppler lidars, especially at higher altitudes. We also developed a new filtering approach for virtual tower scanning strategies. Single Doppler lidars provide reliable wind data over flat terrain.
Thomas Goelles, Tobias Hammer, Stefan Muckenhuber, Birgit Schlager, Jakob Abermann, Christian Bauer, Víctor J. Expósito Jiménez, Wolfgang Schöner, Markus Schratter, Benjamin Schrei, and Kim Senger
Geosci. Instrum. Method. Data Syst., 11, 247–261, https://doi.org/10.5194/gi-11-247-2022, https://doi.org/10.5194/gi-11-247-2022, 2022
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We propose a newly developed modular MObile LIdar SENsor System (MOLISENS) to enable new applications for small industrial light detection and ranging (lidar) sensors. MOLISENS supports both monitoring of dynamic processes and mobile mapping applications. The mobile mapping application of MOLISENS has been tested under various conditions, and results are shown from two surveys in the Lurgrotte cave system in Austria and a glacier cave in Longyearbreen on Svalbard.
Dejan Vasić, Marina Davidović, Ivan Radosavljević, and Đorđe Obradović
Geosci. Instrum. Method. Data Syst., 10, 287–296, https://doi.org/10.5194/gi-10-287-2021, https://doi.org/10.5194/gi-10-287-2021, 2021
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The objective of this paper is to present a new architecture of a solution for object detecting and blurring. Our algorithm is tested on four data sets of panorama images. The percentage of accuracy, i.e., the successfully detected objects of interest, is higher than 97 % for each data set. The proposed algorithm has a wide application for images of different types, surveyed with various purposes, and also for the detection of different types of objects.
Jason Bula, Marc-Henri Derron, and Gregoire Mariethoz
Geosci. Instrum. Method. Data Syst., 9, 385–396, https://doi.org/10.5194/gi-9-385-2020, https://doi.org/10.5194/gi-9-385-2020, 2020
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We developed a method to acquire dense point clouds with a low-cost Velodyne Puck lidar system, without using expensive Global Navigation Satellite System (GNSS) positioning or IMU. We mounted the lidar on a motor to continuously change the scan direction, leading to a significant increase in the point cloud density. The system was compared with a more expensive system based on IMU registration and a SLAM algorithm. The alignment between acquisitions with those two systems is within 2 m.
Cited articles
Alvarez, J. M., Vaughan, M. A., Hostetler, C. A., Hunt, W. H., and Winker,
D. M.: Calibration Technique for Polarization-Sensitive Lidars, J.
Atmos. Ocean. Tech., 23, 683–699,
https://doi.org/10.1175/JTECH1872.1, 2006. a
Andrade, M. D. F., Kumar, P., de Freitas, E. D., Ynoue, R. Y., Martins, J.,
Martins, L. D., Nogueira, T., Perez-Martinez, P., de Miranda, R. M.,
Albuquerque, T., Gonçalves, F. L. T., Oyama, B., and Zhang, Y.: Air quality
in the megacity of São Paulo: Evolution over the last 30 years and
future perspectives, Atmos. Environ., 159, 66–82,
https://doi.org/10.1016/j.atmosenv.2017.03.051, 2017. a
Ansmann, A. and Müller, D.: Lidar: Range-Resolved Optical Remote Sensing of
the Atmosphere, chap. Lidar and Atmospheric Aerosol Particles,
Springer New York, New York, NY, 105–141, https://doi.org/10.1007/0-387-25101-4_4, 2005. a
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. Opt., 31,
7113–7131, https://doi.org/10.1364/AO.31.007113, 1992. a, b
Antuña-Marrero, J. C., Landulfo, E., Estevan, R., Barja, B., Robock, A.,
Wolfram, E., Ristori, P., Clemesha, B., Zaratti, F., Forno, R., Armandillo,
E., Álvaro E. Bastidas, Ángel M. de Frutos Baraja, Whiteman, D. N., Quel,
E., Barbosa, H. M. J., Lopes, F., Montilla-Rosero, E., and Guerrero-Rascado,
J. L.: LALINET: The First Latin American–Born Regional Atmospheric
Observational Network, B. Am. Meteorol. Soc., 98,
1255–1275, https://doi.org/10.1175/BAMS-D-15-00228.1, 2017. a
Artaxo, P., Rizzo, L. V., Brito, J. F., Barbosa, H. M. J., Arana, A., Sena,
E. T., Cirino, G. G., Bastos, W., Martin, S. T., and Andreae, M. O.:
Atmospheric aerosols in Amazonia and land use change: from natural biogenic
to biomass burning conditions, Faraday Discuss., 165, 203–235,
https://doi.org/10.1039/c3fd00052d, 2013. a
Baars, H., Ansmann, A., Althausen, D., Engelmann, R., Heese, B., Müller, D.,
Artaxo, P., Paixao, M., Pauliquevis, T., and Souza, R.: Aerosol profiling
with lidar in the Amazon Basin during the wet and dry season: Aerosol
profiling in Amazonia, J. Geophys. Res.-Atmos.,
117, D21201, https://doi.org/10.1029/2012JD018338, 2012. a
Baars, H., Kanitz, T., Engelmann, R., Althausen, D., Heese, B., Komppula, M., Preißler, J., Tesche, M., Ansmann, A., Wandinger, U., Lim, J.-H., Ahn, J. Y., Stachlewska, I. S., Amiridis, V., Marinou, E., Seifert, P., Hofer, J., Skupin, A., Schneider, F., Bohlmann, S., Foth, A., Bley, S., Pfüller, A., Giannakaki, E., Lihavainen, H., Viisanen, Y., Hooda, R. K., Pereira, S. N., Bortoli, D., Wagner, F., Mattis, I., Janicka, L., Markowicz, K. M., Achtert, P., Artaxo, P., Pauliquevis, T., Souza, R. A. F., Sharma, V. P., van Zyl, P. G., Beukes, J. P., Sun, J., Rohwer, E. G., Deng, R., Mamouri, R.-E., and Zamorano, F.: An overview of the first decade of PollyNET: an emerging network of automated Raman-polarization lidars for continuous aerosol profiling, Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016, 2016. a
Barbosa, H., Lopes, F., Silva, A., Nisperuza, D., Barja, B., Ristori, P.,
Gouveia, D., Jimenez, C., Montilla, E., Mariano, G., Landulfo, E., Bastidas,
A., and Quel, E.: The first ALINE measurements and intercomparison exercise
on lidar inversion algorithms, Optica Pura y Aplicada, 47, 99–108,
https://doi.org/10.7149/OPA.47.2.99, 2014a. a
Barbosa, H. M. J., Barja, B., Pauliquevis, T., Gouveia, D. A., Artaxo, P., Cirino, G. G., Santos, R. M. N., and Oliveira, A. B.: A permanent Raman lidar station in the Amazon: description, characterization, and first results, Atmos. Meas. Tech., 7, 1745–1762, https://doi.org/10.5194/amt-7-1745-2014, 2014b. a, b
Böckmann, C., Wandinger, U., Ansmann, A., Bösenberg, J., Amiridis, V.,
Boselli, A., Delaval, A., Tomasi, F. D., Frioud, M., Grigorov, I. V.,
Hågård, A., Horvat, M., Iarlori, M., Komguem, L., Kreipl, S.,
Larchevêque, G., Matthias, V., Papayannis, A., Pappalardo, G.,
Rocadenbosch, F., Rodrigues, J. A., Schneider, J., Shcherbakov, V., and
Wiegner, M.: Aerosol lidar intercomparison in the framework of the EARLINET
project. 2. Aerosol backscatter algorithms, Appl. Opt., 43, 977–989,
https://doi.org/10.1364/AO.43.000977, 2004. a
Córdoba-Jabonero, C., Sorribas, M., Guerrero-Rascado, J. L., Adame, J. A., Hernández, Y., Lyamani, H., Cachorro, V., Gil, M., Alados-Arboledas, L., Cuevas, E., and de la Morena, B.: Synergetic monitoring of Saharan dust plumes and potential impact on surface: a case study of dust transport from Canary Islands to Iberian Peninsula, Atmos. Chem. Phys., 11, 3067–3091, https://doi.org/10.5194/acp-11-3067-2011, 2011. a
D'Amico, G., Amodeo, A., Baars, H., Binietoglou, I., Freudenthaler, V., Mattis, I., Wandinger, U., and Pappalardo, G.: EARLINET Single Calculus Chain – overview on methodology and strategy, Atmos. Meas. Tech., 8, 4891–4916, https://doi.org/10.5194/amt-8-4891-2015, 2015. a
Dionisi, D., Barnaba, F., Diémoz, H., Di Liberto, L., and Gobbi, G. P.: A multiwavelength numerical model in support of quantitative retrievals of aerosol properties from automated lidar ceilometers and test applications for AOT and PM10 estimation, Atmos. Meas. Tech., 11, 6013–6042, https://doi.org/10.5194/amt-11-6013-2018, 2018. a
Fernald, F. G.: Analysis of atmospheric lidar observations: some comments,
Appl. Opt., 23, 652–653, https://doi.org/10.1364/AO.23.000652, 1984. a
Freudenthaler, V., Linné, H., Chaikovski, A., Rabus, D., and Groß, S.: EARLINET lidar quality assurance tools, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2017-395, in review, 2018. a
Gouveia, D. A., Barbosa, H. M. J., and Barja, B.: Characterization of cirrus
clouds in central Amazon (2.89∘ S, 59.97∘ W): Firsts results from
observations in 2011, Special Section: VII Workshop on Lidar Measurement in
Latin-America, Opt. Pura Apl., 47, 109–114, https://doi.org/10.7149/OPA.47.2.109,
2014. a
Gouveia, D. A., Barja, B., Barbosa, H. M. J., Seifert, P., Baars, H., Pauliquevis, T., and Artaxo, P.: Optical and geometrical properties of cirrus clouds in Amazonia derived from 1 year of ground-based lidar measurements, Atmos. Chem. Phys., 17, 3619–3636, https://doi.org/10.5194/acp-17-3619-2017, 2017a. a
Gouveia, D. A., Barja, B., Barbosa, H. M. J., Seifert, P., Baars, H., Pauliquevis, T., and Artaxo, P.: Optical and geometrical properties of cirrus clouds in Amazonia derived from 1 year of ground-based lidar measurements, Atmos. Chem. Phys., 17, 3619–3636, https://doi.org/10.5194/acp-17-3619-2017, 2017b. a, b, c
Grigorov, I. and Kolarov, G.: Rayleigh-fit approach applied to improve the
removal of background noise from lidar data, in: 17th International School
on Quantum Electronics: Laser Physics and Applications, edited by: Dreischuh,
T. N. and Daskalova, A. T., International Society for
Optics and Photonics, SPIE, https://doi.org/10.1117/12.2012998, 2013. a
Guerrero-Rascado, J. L., Landulfo, E., Antuña, J. C., de Melo Jorge Barbosa,
H., Barja, B., Álvaro Efrain Bastidas, Bedoya, A. E., da Costa, R. F.,
Estevan, R., Forno, R., Gouveia, D. A., Jiménez, C., Larroza, E. G., da
Silva Lopes, F. J., Montilla-Rosero, E., de Arruda Moreira, G., Nakaema,
W. M., Nisperuza, D., Alegria, D., Múnera, M., Otero, L., Papandrea, S.,
Pallota, J. V., Pawelko, E., Quel, E. J., Ristori, P., Rodrigues, P. F.,
Salvador, J., Sánchez, M. F., and Silva, A.: Latin American Lidar Network
(LALINET) for aerosol research: Diagnosis on network instrumentation, J. Atmos. Sol.-Terr. Phy., 138–139, 112–120,
https://doi.org/10.1016/j.jastp.2016.01.001, 2016. a, b
Holben, B., Eck, T., Slutsker, I., Tanré, D., Buis, J., Setzer, A., Vermote,
E., Reagan, J., Kaufman, Y., Nakajima, T., Lavenu, F., Jankowiak, I., and
Smirnov, A.: AERONET – A Federated Instrument Network and Data Archive for
Aerosol Characterization, Remote Sens. Environ., 66, 1–16,
https://doi.org/10.1016/S0034-4257(98)00031-5, 1998. a
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of Working
Group I to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K.,
Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York,
NY, USA, https://doi.org/10.1017/CBO9781107415324, 2013. a
IPCC: Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge, Cambridge University Press, https://doi.org/10.1017/9781009157896, 2023/ a
Johnson, F. A., Jones, R., McLean, T. P., and Pike, E. R.: Dead-Time
Corrections to Photon Counting Distributions, Phys. Rev.
Lett., 16, 589–592, https://doi.org/10.1103/PhysRevLett.16.589, 1966. a
Klett, J. D.: Lidar inversion with variable backscatter/extinction ratios,
Appl. Opt., 24, 1638–1643, https://doi.org/10.1364/AO.24.001638, 1985. a, b
Knoll, G. F.: Radiation detection and measurement, edited by: Hoboken, N. J., John Wiley, 4th edn.,
ISBN 9780470131480, 2010. a
Landulfo, E., da Silva Lopes, F. J., de Arruda Moreira, G., Marques, M. T. A.,
Osneide, M., Antuña, J. C., Arredondo, R. E., Guerrero Rascado, J. L.,
Alados-Arboledas, L., Bastidas, A., Nisperuza, D., Bedoya, A., Múnera, M.,
Alegría, D., Forno, R. N., Sánchez, M. F., Lazcano, O., Montilla-Rosero,
E., Silva, A., Jimenez, C., Quel, E., Ristori, P., Otero, L., Barbosa, H. M.,
Gouveia, D. A., and Barja, B.: ALINE/LALINET Network Status, EPJ Web
Conf., 119, 19004, https://doi.org/10.1051/epjconf/201611919004, 2016. a
Landulfo, E., Cacheffo, A., Yoshida, A. C., Gomes, A. A., da Silva Lopes,
F. J., de Arruda Moreira, G., da Silva, J. J., Andrioli, V., Pimenta, A.,
Wang, C., Xu, J., Martins, M. P. P., Batista, P., de Melo Jorge Barbosa, H.,
Gouveia, D. A., González, B. B., Zamorano, F., Quel, E., Pereira, C.,
Wolfram, E., Casasola, F. I., Orte, F., Salvador, J. O., Pallotta, J. V.,
Otero, L. A., Prieto, M., Ristori, P. R., Brusca, S., Estupiñan, J. H. R.,
Barrera, E. S., Antuña-Marrero, J. C., Forno, R., Andrade, M., Hoelzemann,
J. J., Guedes, A. G., Sousa, C. T., dos Santos Oliveira, D. C. F., de Souza
Fernandes Duarte, E., da Silva, M. P. A., and da Silva Santos, R. S.: Lidar
Observations in South America. Part II – Troposphere, in: Remote Sensing,
edited by: Hammond, A. and Keleher, P., Chap. 2, IntechOpen, Rijeka,
https://doi.org/10.5772/intechopen.95451, 2020. a, b, c
Lewis, J. R., Campbell, J. R., Welton, E. J., Stewart, S. A., and Haftings,
P. C.: Overview of MPLNET Version 3 Cloud Detection, J.
Atmos. Ocean. Tech., 33, 2113–2134,
https://doi.org/10.1175/JTECH-D-15-0190.1, 2016. a
Mather, J. M.: Atmospheric Radiation Measurement (ARM) User Facility 2020
Decadal Vision, Tech. Rep. DOE/SC-ARM-20-014, https://doi.org/10.2172/1782812,
2021. a
Nascimento, J. P., Barbosa, H. M. J., Banducci, A. L., Rizzo, L. V., Vara-Vela,
A. L., Meller, B. B., Gomes, H., Cezar, A., Franco, M. A., Ponczek, M.,
Wolff, S., Bela, M. M., and Artaxo, P.: Major Regional-Scale Production
of O3 and Secondary Organic Aerosol in Remote
Amazon Regions from the Dynamics and Photochemistry of Urban and
Forest Emissions, Environ. Sci. Technol., 56, 9924–9935,
https://doi.org/10.1021/acs.est.2c01358, 2022. a
National Academies of Sciences, Engineering, and Medicine: Thriving on Our
Changing, Planet: A Decadal Strategy for Earth Observation from
Space, National Academies Press, Washington, D.C., https://doi.org/10.17226/24938,
24938 pp., 2018. a
National Geophysical Data Center: U.S. Standard Atmosphere (1976),
Planet. Space Sci., 40, 553–554,
https://doi.org/10.1016/0032-0633(92)90203-Z, 1992. a
Newsom, R. K., Turner, D. D., Mielke, B., Clayton, M., Ferrare, R., and
Sivaraman, C.: Simultaneous analog and photon counting detection for Raman
lidar, Appl. Opt., 48, 3903, https://doi.org/10.1364/AO.48.003903, 2009. a
Pallotta, J. V., Carvalho, S., Lopez, F., Cacheffo, A., Landulfo, E., and
Barbosa, H.: Lidar Processing Pipeline (LPP), Zenodo [code],
https://doi.org/10.5281/zenodo.7982889, 2023. a
Pappalardo, G., Amodeo, A., Pandolfi, M., Wandinger, U., Ansmann, A.,
Bösenberg, J., Matthias, V., Amiridis, V., De Tomasi, F., Frioud, M.,
Larlori, M., Komguem, L., Papayannis, A., Rocadenbosch, F., and Wang, X.:
Aerosol Lidar Intercomparison in the Framework of the EARLINET Project. 3.
Raman Lidar Algorithm for Aerosol Extinction, Backscatter, and Lidar Ratio,
Appl. Opt., 43, 5370–85, https://doi.org/10.1364/AO.43.005370, 2004. a, b, c
Perrone, M. R., Lorusso, A., and Romano, S.: Diurnal and nocturnal aerosol
properties by AERONET sun-sky-lunar photometer measurements along four years,
Atmos. Res., 265, 105889,
https://doi.org/10.1016/j.atmosres.2021.105889, 2022. a
Press, W. H.: Numerical recipes: the art of scientific computing,
Cambridge University Press, Cambridge, UK, New York, 3rd edn., ISBN 0521431085, 2007. a
Reagan, J., McCormick, M., and SPinhirne, J.: Lidar sensing of aerosols and
clouds in the troposphere and stratosphere, P. IEEE, 77,
433–448, https://doi.org/10.1109/5.24129, 1989. a
Ribeiro, F. N., de Oliveira, A. P., Soares, J., de Miranda, R. M., Barlage, M.,
and Chen, F.: Effect of sea breeze propagation on the urban boundary layer of
the metropolitan region of Sao Paulo, Brazil, Atmos. Res.,
214, 174–188, https://doi.org/10.1016/j.atmosres.2018.07.015, 2018. a
Rodrigues, P. F., Landulfo, E., Gandu, A. W., and Lopes, F. J. S.: Assessment
of aerosol hygroscopic growth using an elastic LIDAR and BRAMS simulation
in urban metropolitan areas, AIP Conf. Proc., 1531, 360–363,
https://doi.org/10.1063/1.4804781, 2013. a
Román, R., Benavent-Oltra, J., Casquero-Vera, J., Lopatin, A., Cazorla, A.,
Lyamani, H., Denjean, C., Fuertes, D., Pérez-Ramírez, D., Torres, B.,
Toledano, C., Dubovik, O., Cachorro, V., de Frutos, A., Olmo, F., and
Alados-Arboledas, L.: Retrieval of aerosol profiles combining sunphotometer
and ceilometer measurements in GRASP code, Atmos. Res., 204,
161–177, https://doi.org/10.1016/j.atmosres.2018.01.021, 2018. a
Sugimoto, N. and Uno, I.: Observation of Asian dust and air-pollution aerosols
using a network of ground-based lidars (ADNet): Realtime data processing
for validation/assimilation of chemical transport models, IOP C.
Ser. Earth Env., 7, 012003,
https://doi.org/10.1088/1755-1307/7/1/012003, 2009. a
Tanaka, L. M. d. S., Satyamurty, P., and Machado, L. A. T.: Diurnal variation
of precipitation in central Amazon Basin, Int. J.
Climatol., 34, 3574–3584, https://doi.org/10.1002/joc.3929, 2014. a
Vaughan, M. A., Young, S. A., Winker, D. M., Powell, K. A., Omar, A. H., Liu,
Z., Hu, Y., and Hostetler, C. A.: Fully automated analysis of space-based
lidar data: an overview of the CALIPSO retrieval algorithms and data
products, in: Laser Radar Techniques for Atmospheric Sensing, edited by:
Singh, U. N., vol. 5575, International Society for Optics and
Photonics, SPIE,, 16–30 https://doi.org/10.1117/12.572024, 2004. a
Wandinger, U., Freudenthaler, V., Baars, H., Amodeo, A., Engelmann, R., Mattis, I., Groß, S., Pappalardo, G., Giunta, A., D'Amico, G., Chaikovsky, A., Osipenko, F., Slesar, A., Nicolae, D., Belegante, L., Talianu, C., Serikov, I., Linné, H., Jansen, F., Apituley, A., Wilson, K. M., de Graaf, M., Trickl, T., Giehl, H., Adam, M., Comerón, A., Muñoz-Porcar, C., Rocadenbosch, F., Sicard, M., Tomás, S., Lange, D., Kumar, D., Pujadas, M., Molero, F., Fernández, A. J., Alados-Arboledas, L., Bravo-Aranda, J. A., Navas-Guzmán, F., Guerrero-Rascado, J. L., Granados-Muñoz, M. J., Preißler, J., Wagner, F., Gausa, M., Grigorov, I., Stoyanov, D., Iarlori, M., Rizi, V., Spinelli, N., Boselli, A., Wang, X., Lo Feudo, T., Perrone, M. R., De Tomasi, F., and Burlizzi, P.: EARLINET instrument intercomparison campaigns: overview on strategy and results, Atmos. Meas. Tech., 9, 1001–1023, https://doi.org/10.5194/amt-9-1001-2016, 2016.
a, b
Wang, Z. and Menenti, M.: Challenges and Opportunities in Lidar Remote Sensing,
Front. Remote Sens., 2, 641723, https://doi.org/10.3389/frsen.2021.641723, 2021. a
Welton, E. J. and Campbell, J. R.: Micropulse Lidar Signals: Uncertainty
Analysis, J. Atmos. Ocean. Tech., 19, 2089–2094,
https://doi.org/10.1175/1520-0426(2002)019<2089:MLSUA>2.0.CO;2, 2002. a
Welton, E. J., Campbell, J. R., Spinhirne, J. D., and Scott III, V. S.: Global
monitoring of clouds and aerosols using a network of micropulse lidar
systems, in: Lidar Remote Sensing for Industry and Environment Monitoring,
edited by: Singh, U. N., Asai, K., Ogawa, T., Singh, U. N., Itabe, T., and
Sugimoto, N., Vol. 4153, International Society for Optics and
Photonics, SPIE, 151–158, https://doi.org/10.1117/12.417040, 2001. a
Whiteman, D. N., Melfi, S. H., and Ferrare, R. A.: Raman lidar system for the
measurement of water vapor and aerosols in the Earth’s atmosphere,
Appl. Opt., 31, 3068, https://doi.org/10.1364/AO.31.003068, 1992. a
Whiteman, D. N., Demoz, B., Rush, K., Schwemmer, G., Gentry, B., Di Girolamo,
P., Comer, J., Veselovskii, I., Evans, K., Melfi, S. H., Wang, Z., Cadirola,
M., Mielke, B., Venable, D., and Van Hove, T.: Raman Lidar Measurements
during the International H2O Project. Part I: Instrumentation and
Analysis Techniques, J. Atmos. Ocean. Tech., 23,
157–169, https://doi.org/10.1175/JTECH1838.1, 2006. a
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M.,
Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E.,
Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O.,
Edmunds, S., Evelo, C. T., Finkers, R., Gonzalez-Beltran, A., Gray, A. J.,
Groth, P., Goble, C., Grethe, J. S., Heringa, J., ’t Hoen, P. A., Hooft,
R., Kuhn, T., Kok, R., Kok, J., Lusher, S. J., Martone, M. E., Mons, A.,
Packer, A. L., Persson, B., Rocca-Serra, P., Roos, M., van Schaik, R.,
Sansone, S.-A., Schultes, E., Sengstag, T., Slater, T., Strawn, G., Swertz,
M. A., Thompson, M., van der Lei, J., van Mulligen, E., Velterop, J.,
Waagmeester, A., Wittenburg, P., Wolstencroft, K., Zhao, J., and Mons, B.:
The FAIR Guiding Principles for scientific data management and
stewardship, Sci. Data, 3, 160018, https://doi.org/10.1038/sdata.2016.18, 2016. a
Short summary
Lidar networks coordinate efforts of different groups, providing guidelines to homogenize retrievals from different instruments. We describe an ongoing effort to develop the Lidar Processing Pipeline (LPP) collaboratively, a collection of tools developed in C/C++ to handle all the steps of a typical lidar analysis. Analysis of simulations and real lidar data showcases the LPP’s features. From this exercise, we draw a roadmap to guide future development, accommodating the needs of our community.
Lidar networks coordinate efforts of different groups, providing guidelines to homogenize...