Articles | Volume 17, issue 3
https://doi.org/10.5194/amt-17-921-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-921-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Long-term aerosol particle depolarization ratio measurements with HALO Photonics Doppler lidar
Finnish Meteorological Institute, Helsinki, 00101, Finland
Hannah Lobo
Finnish Meteorological Institute, Helsinki, 00101, Finland
Ewan J. O'Connor
Finnish Meteorological Institute, Helsinki, 00101, Finland
Ville Vakkari
Finnish Meteorological Institute, Helsinki, 00101, Finland
Atmospheric Chemistry Research Group, Chemical Resource Beneficiation, North-West University, Potchefstroom, 2520, South Africa
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Sami Daniel Harni, Lasse Johansson, Jarkko Ville Niemi, Ville Silvonen, Juan Andrés Casquero-Vera, Anu Kousa, Krista Luoma, Viet Le, David Brus, Konstantinos Doulgeris, Topi Rönkkö, Hanna Manninen, Tuukka Petäjä, and Hilkka Timonen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1423, https://doi.org/10.5194/egusphere-2025-1423, 2025
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The 3-month measurement campaign at Espoo, Finland, in spring 2023. The measurement campaign studied the effect of the noise barrier on pollutant concentration gradients on one side of a major highway. The studied pollutants included PM10, PM2.5, lung deposited surface area (LDSA), particle number concentration (PNC), NO2, and black carbon (BC). The noise barrier was found to be effective in reducing, especially the concentration of particulate pollutants.
Viet Le, Konstantinos Matthaios Doulgeris, Mika Komppula, John Backman, Gholamhossein Bagheri, Eberhard Bodenschatz, and David Brus
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-148, https://doi.org/10.5194/essd-2025-148, 2025
Preprint withdrawn
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This manuscript presents datasets collected during the Pallas Cloud Experiment in northern Finland during the autumn of 2022. We provide an overview of the payload that measured meteorological, cloud, and aerosol properties, and was deployed on tethered balloon systems across 21 flights. Additionally, we describe the datasets obtained, including details of the instruments on the payload.
David Brus, Viet Le, Joel Kuula, and Konstantinos Doulgeris
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-61, https://doi.org/10.5194/essd-2025-61, 2025
Revised manuscript accepted for ESSD
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This manuscript provides datasets collected during Pallas Cloud Experiment campaign in norther Finland during the autumn of 2022. We provided an overview of the custom-built drone backpack for air quality and atmospheric state variables carried on top of the consumer-grade drone (DJI Mavic 2 pro). We described the flight strategies, and provided an overview of the datasets obtained, including a description of the measurement against the reference for data validation.
Simo Tukiainen, Tuomas Siipola, Niko Leskinen, and Ewan O'Connor
Earth Syst. Sci. Data, 17, 3797–3806, https://doi.org/10.5194/essd-17-3797-2025, https://doi.org/10.5194/essd-17-3797-2025, 2025
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Measurement campaigns are crucial for advancing the understanding of complex cloud–aerosol interactions in the atmosphere. Ground-based remote sensing measurements were conducted in Kenttärova, Finland, during the Pallas Cloud Experiment 2022 campaign. These measurements were processed using the Cloudnet methodology, and the data are available through the ACTRIS Cloudnet data portal.
Aino Ovaska, Elio Rauth, Daniel Holmberg, Paulo Artaxo, John Backman, Benjamin Bergmans, Don Collins, Marco Aurélio Franco, Shahzad Gani, Roy M. Harrison, Rakes K. Hooda, Tareq Hussein, Antti-Pekka Hyvärinen, Kerneels Jaars, Adam Kristensson, Markku Kulmala, Lauri Laakso, Ari Laaksonen, Nikolaos Mihalopoulos, Colin O'Dowd, Jakub Ondracek, Tuukka Petäjä, Kristina Plauškaitė, Mira Pöhlker, Ximeng Qi, Peter Tunved, Ville Vakkari, Alfred Wiedensohler, Kai Puolamäki, Tuomo Nieminen, Veli-Matti Kerminen, Victoria A. Sinclair, and Pauli Paasonen
Aerosol Research Discuss., https://doi.org/10.5194/ar-2025-18, https://doi.org/10.5194/ar-2025-18, 2025
Preprint under review for AR
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We trained machine learning models to estimate the number of aerosol particles large enough to form clouds and generated daily estimates for the entire globe. The models performed well in many continental regions but struggled in remote and marine areas. Still, this approach offers a way to quantify these particles in areas that lack direct measurements, helping us understand their influence on clouds and climate on a global scale.
Arya Mukherjee, Anni Hartikainen, Markus Somero, Viljami Luostari, Mika Ihalainen, Christopher P. Rüger, Timo Kekäläinen, Ville H. Nissinen, Luis M. F. Barreira, Hanna Koponen, Tuukka Kokkola, Delun Li, Lejish Vettikkat, Pasi Yli-Pirilä, Muhammad Shahzaib, Meri M. Ruppel, Ville Vakkari, Kerneels Jaars, Stefan J. Siebert, Angela Buchholz, Kajar Köster, Pieter G. van Zyl, Hilkka Timonen, Niko Kinnunen, Janne Jänis, Annele Virtanen, Aki Virkkula, and Olli Sippula
EGUsphere, https://doi.org/10.5194/egusphere-2025-2759, https://doi.org/10.5194/egusphere-2025-2759, 2025
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Warming climate is predicted to increase boreal and peatland fires in Northern Eurasia. Limited studies have characterized light absorbing aerosol emissions from these biomasses, thus necessitating this work. Brown carbon (BrC) emitted from laboratory-scale biomass burning had weak light absorptivities based on their complex refractive index values. A combustion temperature dependent light absorptivity continuum existed for emitted BrC. Photochemical aging decreased BrC light absorptivity.
John Backman, Krista Luoma, Henri Servomaa, Ville Vakkari, and David Brus
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-284, https://doi.org/10.5194/essd-2025-284, 2025
Preprint under review for ESSD
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This work describes the in-situ aerosol measurements at the Arctic Sammaltunturi measurement station in Pallas in northern Finland. This data paper describes the instruments and the data post processing of key aerosol particle measurements that are relevant for cloud properties. Data reported here are part of the Pallas Cloud Experiment in 2022 (PaCE2022).
Sami Daniel Harni, Lasse Johansson, Jarkko Ville Niemi, Ville Silvonen, Juan Andrés Casquero-Vera, Anu Kousa, Krista Luoma, Viet Le, David Brus, Konstantinos Doulgeris, Topi Rönkkö, Hanna Manninen, Tuukka Petäjä, and Hilkka Timonen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1423, https://doi.org/10.5194/egusphere-2025-1423, 2025
Short summary
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The 3-month measurement campaign at Espoo, Finland, in spring 2023. The measurement campaign studied the effect of the noise barrier on pollutant concentration gradients on one side of a major highway. The studied pollutants included PM10, PM2.5, lung deposited surface area (LDSA), particle number concentration (PNC), NO2, and black carbon (BC). The noise barrier was found to be effective in reducing, especially the concentration of particulate pollutants.
Viet Le, Konstantinos Matthaios Doulgeris, Mika Komppula, John Backman, Gholamhossein Bagheri, Eberhard Bodenschatz, and David Brus
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-148, https://doi.org/10.5194/essd-2025-148, 2025
Preprint withdrawn
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This manuscript presents datasets collected during the Pallas Cloud Experiment in northern Finland during the autumn of 2022. We provide an overview of the payload that measured meteorological, cloud, and aerosol properties, and was deployed on tethered balloon systems across 21 flights. Additionally, we describe the datasets obtained, including details of the instruments on the payload.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
Atmos. Meas. Tech., 18, 1355–1371, https://doi.org/10.5194/amt-18-1355-2025, https://doi.org/10.5194/amt-18-1355-2025, 2025
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A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall buildings during a period of 1 year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
Ioanna Tsikoudi, Eleni Marinou, Maria Tombrou, Eleni Giannakaki, Emmanouil Proestakis, Konstantinos Rizos, Ville Vakkari, and Vassilis Amiridis
EGUsphere, https://doi.org/10.5194/egusphere-2025-1105, https://doi.org/10.5194/egusphere-2025-1105, 2025
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The lowest part of the atmosphere plays a critical role in weather and climate. Using groundbased and space lidar, radiosondes and model data, we analyzed how dust and local wind conditions influence its height over the tropical Atlantic. We found that different conditions, as well as different methods yield varying results, highlighting challenges in defining the boundary layer top. Understanding these differences improves climate models and our knowledge of atmospheric dynamics in this region.
David Brus, Viet Le, Joel Kuula, and Konstantinos Doulgeris
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-61, https://doi.org/10.5194/essd-2025-61, 2025
Revised manuscript accepted for ESSD
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This manuscript provides datasets collected during Pallas Cloud Experiment campaign in norther Finland during the autumn of 2022. We provided an overview of the custom-built drone backpack for air quality and atmospheric state variables carried on top of the consumer-grade drone (DJI Mavic 2 pro). We described the flight strategies, and provided an overview of the datasets obtained, including a description of the measurement against the reference for data validation.
Maria Filioglou, Petri Tiitta, Xiaoxia Shang, Ari Leskinen, Pasi Ahola, Sanna Pätsi, Annika Saarto, Ville Vakkari, Uula Isopahkala, and Mika Komppula
Atmos. Chem. Phys., 25, 1639–1657, https://doi.org/10.5194/acp-25-1639-2025, https://doi.org/10.5194/acp-25-1639-2025, 2025
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Every year a vast number of people experience allergic reactions due to exposure to airborne pollen. These symptoms are concentration dependent; thus accurate information about the pollen load in the atmosphere is essential. Moreover, pollen grains and fragments of it are likely to contribute to cloud processes and suppress precipitation. Here, we estimate the concentration and cloud-relevant parameters of birch pollen in the atmosphere using observations from a PollyXT and a CL61 ceilometer.
Sasu Karttunen, Matthias Sühring, Ewan O'Connor, and Leena Järvi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-235, https://doi.org/10.5194/gmd-2024-235, 2024
Revised manuscript accepted for GMD
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This paper presents PALM-SLUrb, a single-layer urban canopy model for the PALM system, designed to simulate urban-atmosphere interactions without resolving flow around individual buildings. The model is described in detail and evaluated against grid-resolved urban canopy simulations, demonstrating its ability to model urban surfaces accurately. By bridging the gap between computational efficiency and physical detail, PALM-SLUrb broadens PALM's potential for urban climate research.
Johanna Tjernström, Michael Gallagher, Jareth Holt, Gunilla Svensson, Matthew D. Shupe, Jonathan J. Day, Lara Ferrighi, Siri Jodha Khalsa, Leslie M. Hartten, Ewan O'Connor, Zen Mariani, and Øystein Godøy
EGUsphere, https://doi.org/10.5194/egusphere-2024-2088, https://doi.org/10.5194/egusphere-2024-2088, 2024
Preprint archived
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The value of numerical weather predictions can be enhanced in several ways, one is to improve the representations of small-scale processes in models. To understand what needs to be improved, the model results need to be evaluated. Following standardized principles, a file format has been defined to be as similar as possible for both observational and model data. Python packages and toolkits are presented as a community resource in the production of the files and evaluation analysis.
Zoé Brasseur, Julia Schneider, Janne Lampilahti, Ville Vakkari, Victoria A. Sinclair, Christina J. Williamson, Carlton Xavier, Dmitri Moisseev, Markus Hartmann, Pyry Poutanen, Markus Lampimäki, Markku Kulmala, Tuukka Petäjä, Katrianne Lehtipalo, Erik S. Thomson, Kristina Höhler, Ottmar Möhler, and Jonathan Duplissy
Atmos. Chem. Phys., 24, 11305–11332, https://doi.org/10.5194/acp-24-11305-2024, https://doi.org/10.5194/acp-24-11305-2024, 2024
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Ice-nucleating particles (INPs) strongly influence the formation of clouds by initiating the formation of ice crystals. However, very little is known about the vertical distribution of INPs in the atmosphere. Here, we present aircraft measurements of INP concentrations above the Finnish boreal forest. Results show that near-surface INPs are efficiently transported and mixed within the boundary layer and occasionally reach the free troposphere.
Romanos Foskinis, Ghislain Motos, Maria I. Gini, Olga Zografou, Kunfeng Gao, Stergios Vratolis, Konstantinos Granakis, Ville Vakkari, Kalliopi Violaki, Andreas Aktypis, Christos Kaltsonoudis, Zongbo Shi, Mika Komppula, Spyros N. Pandis, Konstantinos Eleftheriadis, Alexandros Papayannis, and Athanasios Nenes
Atmos. Chem. Phys., 24, 9827–9842, https://doi.org/10.5194/acp-24-9827-2024, https://doi.org/10.5194/acp-24-9827-2024, 2024
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Analysis of modeling, in situ, and remote sensing measurements reveals the microphysical state of orographic clouds and their response to aerosol from the boundary layer and free troposphere. We show that cloud response to aerosol is robust, as predicted supersaturation and cloud droplet number levels agree with those determined from in-cloud measurements. The ability to determine if clouds are velocity- or aerosol-limited allows for novel model constraints and remote sensing products.
Jutta Kesti, Ewan J. O'Connor, Anne Hirsikko, John Backman, Maria Filioglou, Anu-Maija Sundström, Juha Tonttila, Heikki Lihavainen, Hannele Korhonen, and Eija Asmi
Atmos. Chem. Phys., 24, 9369–9386, https://doi.org/10.5194/acp-24-9369-2024, https://doi.org/10.5194/acp-24-9369-2024, 2024
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The study combines aerosol particle measurements at the surface and vertical profiling of the atmosphere with a scanning Doppler lidar to investigate how particle transportation together with boundary layer evolution can affect particle and SO2 concentrations at the surface in the Arabian Peninsula region. The instrumentation enabled us to see elevated nucleation mode particle and SO2 concentrations at the surface when air masses transported from polluted areas are mixed in the boundary layer.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
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During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Christoffer Hallgren, Jeanie A. Aird, Stefan Ivanell, Heiner Körnich, Ville Vakkari, Rebecca J. Barthelmie, Sara C. Pryor, and Erik Sahlée
Wind Energ. Sci., 9, 821–840, https://doi.org/10.5194/wes-9-821-2024, https://doi.org/10.5194/wes-9-821-2024, 2024
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Knowing the wind speed across the rotor of a wind turbine is key in making good predictions of the power production. However, models struggle to capture both the speed and the shape of the wind profile. Using machine learning methods based on the model data, we show that the predictions can be improved drastically. The work focuses on three coastal sites, spread over the Northern Hemisphere (the Baltic Sea, the North Sea, and the US Atlantic coast) with similar results for all sites.
Christoffer Hallgren, Heiner Körnich, Stefan Ivanell, Ville Vakkari, and Erik Sahlée
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-129, https://doi.org/10.5194/wes-2023-129, 2023
Preprint withdrawn
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Sometimes, the wind changes direction between the bottom and top part of a wind turbine. This affects both the power production and the loads on the turbine. In this study, a climatology of pronounced changes in wind direction across the rotor is created, focusing on Scandinavia. The weather conditions responsible for these changes in wind direction are investigated and the climatology is compared to measurements from two coastal sites, indicating an underestimation by the climatology.
Simo Hakala, Ville Vakkari, Heikki Lihavainen, Antti-Pekka Hyvärinen, Kimmo Neitola, Jenni Kontkanen, Veli-Matti Kerminen, Markku Kulmala, Tuukka Petäjä, Tareq Hussein, Mamdouh I. Khoder, Mansour A. Alghamdi, and Pauli Paasonen
Atmos. Chem. Phys., 23, 9287–9321, https://doi.org/10.5194/acp-23-9287-2023, https://doi.org/10.5194/acp-23-9287-2023, 2023
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Things are not always as they first seem in ambient aerosol measurements. Observations of decreasing particle sizes are often interpreted as resulting from particle evaporation. We show that such observations can counterintuitively be explained by particles that are constantly growing in size. This requires one to account for the previous movements of the observed air. Our explanation implies a larger number of larger particles, meaning more significant effects of aerosols on climate and health.
Maria Filioglou, Ari Leskinen, Ville Vakkari, Ewan O'Connor, Minttu Tuononen, Pekko Tuominen, Samuli Laukkanen, Linnea Toiviainen, Annika Saarto, Xiaoxia Shang, Petri Tiitta, and Mika Komppula
Atmos. Chem. Phys., 23, 9009–9021, https://doi.org/10.5194/acp-23-9009-2023, https://doi.org/10.5194/acp-23-9009-2023, 2023
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Pollen impacts climate and public health, and it can be detected in the atmosphere by lidars which measure the linear particle depolarization ratio (PDR), a shape-relevant optical parameter. As aerosols also cause depolarization, surface aerosol and pollen observations were combined with measurements from ground-based lidars operating at different wavelengths to determine the optical properties of birch and pine pollen and quantify their relative contribution to the PDR.
Gillian Young McCusker, Jutta Vüllers, Peggy Achtert, Paul Field, Jonathan J. Day, Richard Forbes, Ruth Price, Ewan O'Connor, Michael Tjernström, John Prytherch, Ryan Neely III, and Ian M. Brooks
Atmos. Chem. Phys., 23, 4819–4847, https://doi.org/10.5194/acp-23-4819-2023, https://doi.org/10.5194/acp-23-4819-2023, 2023
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In this study, we show that recent versions of two atmospheric models – the Unified Model and Integrated Forecasting System – overestimate Arctic cloud fraction within the lower troposphere by comparison with recent remote-sensing measurements made during the Arctic Ocean 2018 expedition. The overabundance of cloud is interlinked with the modelled thermodynamic structure, with strong negative temperature biases coincident with these overestimated cloud layers.
Pyry Pentikäinen, Ewan J. O'Connor, and Pablo Ortiz-Amezcua
Geosci. Model Dev., 16, 2077–2094, https://doi.org/10.5194/gmd-16-2077-2023, https://doi.org/10.5194/gmd-16-2077-2023, 2023
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We used Doppler lidar to evaluate the wind profiles generated by a weather forecast model. We first compared the Doppler lidar observations with co-located radiosonde profiles, and they agree well. The model performs best over marine and coastal locations. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.
Konstantinos Matthaios Doulgeris, Ville Vakkari, Ewan J. O'Connor, Veli-Matti Kerminen, Heikki Lihavainen, and David Brus
Atmos. Chem. Phys., 23, 2483–2498, https://doi.org/10.5194/acp-23-2483-2023, https://doi.org/10.5194/acp-23-2483-2023, 2023
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We investigated how different long-range-transported air masses can affect the microphysical properties of low-level clouds in a clean subarctic environment. A connection was revealed. Higher values of cloud droplet number concentrations were related to continental air masses, whereas the lowest values of number concentrations were related to marine air masses. These were characterized by larger cloud droplets. Clouds in all regions were sensitive to increases in cloud number concentration.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
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Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Matti Räsänen, Mika Aurela, Ville Vakkari, Johan P. Beukes, Juha-Pekka Tuovinen, Pieter G. Van Zyl, Miroslav Josipovic, Stefan J. Siebert, Tuomas Laurila, Markku Kulmala, Lauri Laakso, Janne Rinne, Ram Oren, and Gabriel Katul
Hydrol. Earth Syst. Sci., 26, 5773–5791, https://doi.org/10.5194/hess-26-5773-2022, https://doi.org/10.5194/hess-26-5773-2022, 2022
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The productivity of semiarid grazed grasslands is linked to the variation in rainfall and transpiration. By combining carbon dioxide and water flux measurements, we show that the annual transpiration is nearly constant during wet years while grasses react quickly to dry spells and drought, which reduce transpiration. The planning of annual grazing strategies could consider the early-season rainfall frequency that was linked to the portion of annual transpiration.
Jenna Ritvanen, Ewan O'Connor, Dmitri Moisseev, Raisa Lehtinen, Jani Tyynelä, and Ludovic Thobois
Atmos. Meas. Tech., 15, 6507–6519, https://doi.org/10.5194/amt-15-6507-2022, https://doi.org/10.5194/amt-15-6507-2022, 2022
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Doppler lidars and weather radars provide accurate wind measurements, with Doppler lidar usually performing better in dry weather conditions and weather radar performing better when there is precipitation. Operating both instruments together should therefore improve the overall performance. We investigate how well a co-located Doppler lidar and X-band radar perform with respect to various weather conditions, including changes in horizontal visibility, cloud altitude, and precipitation.
Carlton Xavier, Metin Baykara, Robin Wollesen de Jonge, Barbara Altstädter, Petri Clusius, Ville Vakkari, Roseline Thakur, Lisa Beck, Silvia Becagli, Mirko Severi, Rita Traversi, Radovan Krejci, Peter Tunved, Mauro Mazzola, Birgit Wehner, Mikko Sipilä, Markku Kulmala, Michael Boy, and Pontus Roldin
Atmos. Chem. Phys., 22, 10023–10043, https://doi.org/10.5194/acp-22-10023-2022, https://doi.org/10.5194/acp-22-10023-2022, 2022
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The focus of this work is to study and improve our understanding of processes involved in the formation and growth of new particles in a remote Arctic marine environment. We run the 1D model ADCHEM along air mass trajectories arriving at Ny-Ålesund in May 2018. The model finds that ion-mediated H2SO4–NH3 nucleation can explain the observed new particle formation at Ny-Ålesund. The growth of particles is driven via H2SO4 condensation and formation of methane sulfonic acid in the aqueous phase.
Sasu Karttunen, Ewan O'Connor, Olli Peltola, and Leena Järvi
Atmos. Meas. Tech., 15, 2417–2432, https://doi.org/10.5194/amt-15-2417-2022, https://doi.org/10.5194/amt-15-2417-2022, 2022
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To study the complex structure of the lowest tens of metres of atmosphere in urban areas, measurement methods with great spatial and temporal coverage are needed. In our study, we analyse measurements with a promising and relatively new method, distributed temperature sensing, capable of providing detailed information on the near-surface atmosphere. We present multiple ways to utilise these kinds of measurements, as well as important considerations for planning new studies using the method.
Mathew Sebastian, Sobhan Kumar Kompalli, Vasudevan Anil Kumar, Sandhya Jose, S. Suresh Babu, Govindan Pandithurai, Sachchidanand Singh, Rakesh K. Hooda, Vijay K. Soni, Jeffrey R. Pierce, Ville Vakkari, Eija Asmi, Daniel M. Westervelt, Antti-Pekka Hyvärinen, and Vijay P. Kanawade
Atmos. Chem. Phys., 22, 4491–4508, https://doi.org/10.5194/acp-22-4491-2022, https://doi.org/10.5194/acp-22-4491-2022, 2022
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Characteristics of particle number size distributions and new particle formation in six locations in India were analyzed. New particle formation occurred frequently during the pre-monsoon (spring) season and it significantly modulates the shape of the particle number size distributions. The contribution of newly formed particles to cloud condensation nuclei concentrations was ~3 times higher in urban locations than in mountain background locations.
Jutta Kesti, John Backman, Ewan J. O'Connor, Anne Hirsikko, Eija Asmi, Minna Aurela, Ulla Makkonen, Maria Filioglou, Mika Komppula, Hannele Korhonen, and Heikki Lihavainen
Atmos. Chem. Phys., 22, 481–503, https://doi.org/10.5194/acp-22-481-2022, https://doi.org/10.5194/acp-22-481-2022, 2022
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In this study we combined aerosol particle measurements at the surface with a scanning Doppler lidar providing vertical profiles of the atmosphere to study the effect of different boundary layer conditions on aerosol particle properties in the understudied Arabian Peninsula region. The instrumentation used in this study enabled us to identify periods when pollution from remote sources was mixed down to the surface and initiated new particle formation in the growing boundary layer.
Clémence Rose, Martine Collaud Coen, Elisabeth Andrews, Yong Lin, Isaline Bossert, Cathrine Lund Myhre, Thomas Tuch, Alfred Wiedensohler, Markus Fiebig, Pasi Aalto, Andrés Alastuey, Elisabeth Alonso-Blanco, Marcos Andrade, Begoña Artíñano, Todor Arsov, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Juan Andrés Casquero-Vera, Sébastien Conil, Konstantinos Eleftheriadis, Olivier Favez, Harald Flentje, Maria I. Gini, Francisco Javier Gómez-Moreno, Martin Gysel-Beer, Anna Gannet Hallar, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Neng-Huei Lin, Hassan Lyamani, Angela Marinoni, Sebastiao Martins Dos Santos, Olga L. Mayol-Bracero, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Jakub Ondracek, Marco Pandolfi, Noemi Pérez, Tuukka Petäjä, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Jean-Philippe Putaud, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Junying Sun, Pierre Tulet, Ville Vakkari, Pieter Gideon van Zyl, Fernando Velarde, Paolo Villani, Stergios Vratolis, Zdenek Wagner, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Vladimir Zdimal, and Paolo Laj
Atmos. Chem. Phys., 21, 17185–17223, https://doi.org/10.5194/acp-21-17185-2021, https://doi.org/10.5194/acp-21-17185-2021, 2021
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Aerosol particles are a complex component of the atmospheric system the effects of which are among the most uncertain in climate change projections. Using data collected at 62 stations, this study provides the most up-to-date picture of the spatial distribution of particle number concentration and size distribution worldwide, with the aim of contributing to better representation of aerosols and their interactions with clouds in models and, therefore, better evaluation of their impact on climate.
Anna Franck, Dmitri Moisseev, Ville Vakkari, Matti Leskinen, Janne Lampilahti, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Meas. Tech., 14, 7341–7353, https://doi.org/10.5194/amt-14-7341-2021, https://doi.org/10.5194/amt-14-7341-2021, 2021
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We proposed a method to derive a convective boundary layer height, using insects in radar observations, and we investigated the consistency of these retrievals among different radar frequencies (5, 35 and 94 GHz). This method can be applied to radars at other measurement stations and serve as additional way to estimate the boundary layer height during summer. The entrainment zone was also observed by the 5 GHz radar above the boundary layer in the form of a Bragg scatter layer.
Philipp G. Eger, Luc Vereecken, Rolf Sander, Jan Schuladen, Nicolas Sobanski, Horst Fischer, Einar Karu, Jonathan Williams, Ville Vakkari, Tuukka Petäjä, Jos Lelieveld, Andrea Pozzer, and John N. Crowley
Atmos. Chem. Phys., 21, 14333–14349, https://doi.org/10.5194/acp-21-14333-2021, https://doi.org/10.5194/acp-21-14333-2021, 2021
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We determine the impact of pyruvic acid photolysis on the formation of acetaldehyde and peroxy radicals during summer and autumn in the Finnish boreal forest using a data-constrained box model. Our results are dependent on the chosen scenario in which the overall quantum yield and the photolysis products are varied. We highlight that pyruvic acid photolysis can be an important contributor to acetaldehyde and peroxy radical formation in remote, forested regions.
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179, https://doi.org/10.5194/amt-14-6159-2021, https://doi.org/10.5194/amt-14-6159-2021, 2021
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The long-range-transported smoke particles from a Canadian wildfire event were observed with a multi-wavelength Raman polarization lidar and a ceilometer over Kuopio, Finland, in June 2019. The optical properties and the mass concentration estimations were reported for such aged smoke aerosols over northern Europe.
Christoffer Hallgren, Stefan Ivanell, Heiner Körnich, Ville Vakkari, and Erik Sahlée
Wind Energ. Sci., 6, 1205–1226, https://doi.org/10.5194/wes-6-1205-2021, https://doi.org/10.5194/wes-6-1205-2021, 2021
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As wind power becomes more popular, there is a growing demand for accurate power production forecasts. In this paper we investigated different methods to improve wind power forecasts for an offshore location in the Baltic Sea, using both simple and more advanced techniques. The performance of the methods is evaluated for different weather conditions. Smoothing the forecast was found to be the best method in general, but we recommend selecting which method to use based on the forecasted weather.
Janne Lampilahti, Katri Leino, Antti Manninen, Pyry Poutanen, Anna Franck, Maija Peltola, Paula Hietala, Lisa Beck, Lubna Dada, Lauriane Quéléver, Ronja Öhrnberg, Ying Zhou, Madeleine Ekblom, Ville Vakkari, Sergej Zilitinkevich, Veli-Matti Kerminen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys., 21, 7901–7915, https://doi.org/10.5194/acp-21-7901-2021, https://doi.org/10.5194/acp-21-7901-2021, 2021
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Using airborne measurements we observed increased number concentrations of sub-25 nm particles in the upper residual layer. These particles may be entrained into the well-mixed boundary layer and observed at the surface. We attribute our observations to new particle formation in the topmost part of the residual layer.
Stephanie Bohlmann, Xiaoxia Shang, Ville Vakkari, Elina Giannakaki, Ari Leskinen, Kari E. J. Lehtinen, Sanna Pätsi, and Mika Komppula
Atmos. Chem. Phys., 21, 7083–7097, https://doi.org/10.5194/acp-21-7083-2021, https://doi.org/10.5194/acp-21-7083-2021, 2021
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Measurements of the multi-wavelength Raman polarization lidar PollyXT and a Halo Photonics StreamLine Doppler lidar have been combined with measurements of pollen type and concentration using a traditional pollen trap at the rural forest site in Vehmasmäki, Finland. Depolarization ratios were measured at three wavelengths. High depolarization ratios were detected during an event with high birch and spruce pollen concentrations and a wavelength dependence of the depolarization ratio was observed.
Ville Vakkari, Holger Baars, Stephanie Bohlmann, Johannes Bühl, Mika Komppula, Rodanthi-Elisavet Mamouri, and Ewan James O'Connor
Atmos. Chem. Phys., 21, 5807–5820, https://doi.org/10.5194/acp-21-5807-2021, https://doi.org/10.5194/acp-21-5807-2021, 2021
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The depolarization ratio is a valuable parameter for aerosol categorization from remote sensing measurements. Here, we introduce particle depolarization ratio measurements at the 1565 nm wavelength, which is substantially longer than previously utilized wavelengths and enhances our capabilities to study the wavelength dependency of the particle depolarization ratio.
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, https://doi.org/10.5194/amt-14-2451-2021, 2021
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The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account for cloud interference with the observations, S5P cloud data products (CLOUD OCRA/ROCINN_CAL, OCRA/ROCINN_CRB, and FRESCO) provide vital input: cloud fraction, cloud height, and cloud optical thickness. Here, S5P cloud parameters are validated by comparing with other satellite sensors (VIIRS, MODIS, and OMI) and with ground-based CloudNet data. The agreement depends on product type and cloud height.
Olli Peltola, Karl Lapo, Ilkka Martinkauppi, Ewan O'Connor, Christoph K. Thomas, and Timo Vesala
Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, https://doi.org/10.5194/amt-14-2409-2021, 2021
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We evaluated the suitability of fiber-optic distributed temperature sensing (DTS) for observing spatial (>25 cm) and temporal (>1 s) details of airflow within and above forests. The DTS measurements could discern up to third-order moments of the flow and observe spatial details of coherent flow motions. Similar measurements are not possible with more conventional measurement techniques. Hence, the DTS measurements will provide key insights into flows close to roughness elements, e.g. trees.
David Brus, Jani Gustafsson, Ville Vakkari, Osku Kemppinen, Gijs de Boer, and Anne Hirsikko
Atmos. Chem. Phys., 21, 517–533, https://doi.org/10.5194/acp-21-517-2021, https://doi.org/10.5194/acp-21-517-2021, 2021
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This paper summarizes Finnish Meteorological Institute and Kansas State University unmanned aerial vehicle measurements during the summer 2018 Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) campaign in the San Luis Valley, providing an overview of the rotorcraft deployed, payloads, scientific goals and flight strategies and presenting observations of atmospheric thermodynamics and aerosol and gas parameters in the vertical column.
Marta Wenta, David Brus, Konstantinos Doulgeris, Ville Vakkari, and Agnieszka Herman
Earth Syst. Sci. Data, 13, 33–42, https://doi.org/10.5194/essd-13-33-2021, https://doi.org/10.5194/essd-13-33-2021, 2021
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Representations of the atmospheric boundary layer over sea ice are a challenge for numerical weather prediction models. To increase our understanding of the relevant processes, a field campaign was carried out over the sea ice in the Baltic Sea from 27 February to 2 March 2020. Observations included 27 unmanned aerial vehicle flights, four photogrammetry missions, and shore-based automatic weather station and lidar wind measurements. The dataset obtained is used to validate model results.
Peggy Achtert, Ewan J. O'Connor, Ian M. Brooks, Georgia Sotiropoulou, Matthew D. Shupe, Bernhard Pospichal, Barbara J. Brooks, and Michael Tjernström
Atmos. Chem. Phys., 20, 14983–15002, https://doi.org/10.5194/acp-20-14983-2020, https://doi.org/10.5194/acp-20-14983-2020, 2020
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We present observations of precipitating and non-precipitating Arctic liquid and mixed-phase clouds during a research cruise along the Russian shelf in summer and autumn of 2014. Active remote-sensing observations, radiosondes, and auxiliary measurements are combined in the synergistic Cloudnet retrieval. Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. About 8 % of all liquid clouds show a liquid water path below the infrared black body limit.
Cited articles
Aaltonen, V., Rodriguez, E., Kazadzis, S., Arola, A., Amiridis, V., Lihavainen, H., and De Leeuw, G.: On the variation of aerosol properties over Finland based on the optical columnar measurements, Atmos. Res., 116, 46–55, https://doi.org/10.1016/j.atmosres.2011.07.014, 2012.
Adams-Groom, B., Emberlin, J., Corden, J., Millington, W., and Mullins, J.: Predicting the start of the birch pollen season at London, Derby and Cardiff, United Kingdom, using a multiple regression model, based on data from 1987 to 1997, Aerobiologia, 18, 117–123, https://doi.org/10.1023/A:1020698023134, 2002.
Alba, F., De La Guardia, C. D., and Comtois, P.: The effect of meteorological parameters on diurnal patterns of airborne olive pollen concentration, Grana, 39, 200–208, https://doi.org/10.1080/00173130051084340, 2000.
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.
Baars, H., Seifert, P., Engelmann, R., and Wandinger, U.: Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements, Atmos. Meas. Tech., 10, 3175–3201, https://doi.org/10.5194/amt-10-3175-2017, 2017.
Baek, J., McLachlan, G. J., and Flack, L. K.: Mixtures of factor analyzers with common factor loadings: Applications to the clustering and visualization of high-dimensional data, IEEE T. Pattern Anal., 32, 1298–1309, https://doi.org/10.1109/TPAMI.2009.149, 2010.
Bartková-Ščevková, J.: The influence of temperature, relative humidity and rainfall on the occurrence of pollen allergens (Betula, Poaceae, Ambrosia artemisiifolia) in the atmosphere of Bratislava (Slovakia), Int. J. Biometeorol., 48, 1–5, https://doi.org/10.1007/s00484-003-0166-2, 2003.
Benedetti, A., Morcrette, J.-J., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S., Mangold, A., Razinger, M., Simmons, A. J., and Suttie, M.: Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation, J. Geophys. Res.-Atmos., 114, D13205, https://doi.org/10.1029/2008JD011115, 2009.
Bohlmann, S., Shang, X., Giannakaki, E., Filioglou, M., Saarto, A., Romakkaniemi, S., and Komppula, M.: Detection and characterization of birch pollen in the atmosphere using a multiwavelength Raman polarization lidar and Hirst-type pollen sampler in Finland, Atmos. Chem. Phys., 19, 14559–14569, https://doi.org/10.5194/acp-19-14559-2019, 2019.
Bohlmann, S., Shang, X., Vakkari, V., Giannakaki, E., Leskinen, A., Lehtinen, K. E. J., Pätsi, S., and Komppula, M.: Lidar depolarization ratio of atmospheric pollen at multiple wavelengths, Atmos. Chem. Phys., 21, 7083–7097, https://doi.org/10.5194/acp-21-7083-2021, 2021.
Brus, D., Gustafsson, J., Vakkari, V., Kemppinen, O., de Boer, G., and Hirsikko, A.: Measurement report: Properties of aerosol and gases in the vertical profile during the LAPSE-RATE campaign, Atmos. Chem. Phys., 21, 517–533, https://doi.org/10.5194/acp-21-517-2021, 2021.
Bucholtz, A.: Rayleigh-scattering calculations for the terrestrial atmosphere, Appl. Opt., 34, 2765–2773, https://doi.org/10.1364/AO.34.002765, 1995.
Burton, S. P., Ferrare, R. A., Hostetler, C. A., Hair, J. W., Rogers, R. R., Obland, M. D., Butler, C. F., Cook, A. L., Harper, D. B., and Froyd, K. D.: Aerosol classification using airborne High Spectral Resolution Lidar measurements – methodology and examples, Atmos. Meas. Tech., 5, 73–98, https://doi.org/10.5194/amt-5-73-2012, 2012.
Burton, S. P., Ferrare, R. A., Vaughan, M. A., Omar, A. H., Rogers, R. R., Hostetler, C. A., and Hair, J. W.: Aerosol classification from airborne HSRL and comparisons with the CALIPSO vertical feature mask, Atmos. Meas. Tech., 6, 1397–1412, https://doi.org/10.5194/amt-6-1397-2013, 2013.
Burton, S. P., Hair, J. W., Kahnert, M., Ferrare, R. A., Hostetler, C. A., Cook, A. L., Harper, D. B., Berkoff, T. A., Seaman, S. T., Collins, J. E., Fenn, M. A., and Rogers, R. R.: Observations of the spectral dependence of linear particle depolarization ratio of aerosols using NASA Langley airborne High Spectral Resolution Lidar, Atmos. Chem. Phys., 15, 13453–13473, https://doi.org/10.5194/acp-15-13453-2015, 2015.
Creamean, J. M., de Boer, G., Telg, H., Mei, F., Dexheimer, D., Shupe, M. D., Solomon, A., and McComiskey, A.: Assessing the vertical structure of Arctic aerosols using balloon-borne measurements, Atmos. Chem. Phys., 21, 1737–1757, https://doi.org/10.5194/acp-21-1737-2021, 2021.
Dailidė, R., Dailidė, G., Razbadauskaitė-Venskė, I., Povilanskas, R., and Dailidienė, I.: Sea-Breeze Front Research Based on Remote Sensing Methods in Coastal Baltic Sea Climate: Case of Lithuania, J. Mar. Sci. Eng., 10, 1779, https://doi.org/10.3390/jmse10111779, 2022.
Di, Q., Wang, Y., Zanobetti, A., Wang, Y., Koutrakis, P., Choirat, C., Dominici, F., and Schwartz, J. D.: Air Pollution and Mortality in the Medicare Population, New Engl. J. Med., 376, 2513–2522, https://doi.org/10.1056/nejmoa1702747, 2017.
Durham, O. C.: The volumetric incidence of atmospheric allergens. I. Specific gravity of pollen grains, J. Allergy, 14, 455–461, https://doi.org/10.1016/S0021-8707(43)90495-2, 1943.
Engelmann, R., Kanitz, T., Baars, H., Heese, B., Althausen, D., Skupin, A., Wandinger, U., Komppula, M., Stachlewska, I. S., Amiridis, V., Marinou, E., Mattis, I., Linné, H., and Ansmann, A.: The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: the neXT generation, Atmos. Meas. Tech., 9, 1767–1784, https://doi.org/10.5194/amt-9-1767-2016, 2016.
Franchi, G. G., Pacini, E., and Rottoli, P.: Pollen grain viability in parietaria judaica l. During the long blooming period and correlation with meteorological conditions and allergic diseases”, Giornale Botanico Italiano, 118, 163–178, https://doi.org/10.1080/11263508409426670, 1984.
Frehlich, R. G. and Kavaya, M. J.: Coherent laser radar performance for general atmospheric refractive turbulence, Appl. Opt., 30, 5325–5352, https://doi.org/10.1364/AO.30.005325, 1991.
Freudenthaler, V., Esselborn, M., Wiegner, M., Heese, B., Tesche, M., Ansmann, A., Müller, D., Althausen, D., Wirth, M., Fix, A., Ehret, G., Knippertz, P., Toledano, C., Gasteiger, J., Garhammer, M., and Seefeldner, M.: Depolarization ratio profiling at several wavelengths in pure Saharan dust during SAMUM 2006, Tellus B, 61, 165–179, https://doi.org/10.1111/j.1600-0889.2008.00396.x, 2009.
Gilissen, L. J. W.: The influence of relative humidity on the swelling of pollen grains in vitro, Planta, 137, 299–301, https://doi.org/10.1007/BF00388166, 1977.
Gonzalez, R. C. and Woods, R. E.: Digital Image Processing, 3rd Edition, Pearson Education, 976 pp., ISBN 9780131687288, 2007.
Granados-Muñoz, M. J., Navas-Guzmán, F., Bravo-Aranda, J. A., Guerrero-Rascado, J. L., Lyamani, H., Valenzuela, A., Titos, G., Fernández-Gálvez, J., and Alados-Arboledas, L.: Hygroscopic growth of atmospheric aerosol particles based on active remote sensing and radiosounding measurements: selected cases in southeastern Spain, Atmos. Meas. Tech., 8, 705–718, https://doi.org/10.5194/amt-8-705-2015, 2015.
Griffiths, P. T., Borlace, J. S., Gallimore, P. J., Kalberer, M., Herzog, M., and Pope, F. D.: Hygroscopic growth and cloud activation of pollen: A laboratory and modelling study, Atmos. Sci. Lett., 13, 289–295, https://doi.org/10.1002/asl.397, 2012.
Groß, S., Tesche, M., Freudenthaler, V., Toledano, C., Wiegner, M., Ansmann, A., Althausen, D., and Seefeldner, M.: Characterization of Saharan dust, marine aerosols and mixtures of biomass-burning aerosols and dust by means of multi-wavelength depolarization and Raman lidar measurements during SAMUM 2, Tellus B, 63, 706–724, https://doi.org/10.1111/j.1600-0889.2011.00556.x, 2011.
Groß, S., Esselborn, M., Weinzierl, B., Wirth, M., Fix, A., and Petzold, A.: Aerosol classification by airborne high spectral resolution lidar observations, Atmos. Chem. Phys., 13, 2487–2505, https://doi.org/10.5194/acp-13-2487-2013, 2013.
Guo, S., Wang, G., Han, L., Song, X., and Yang, W.: COVID-19 CT image denoising algorithm based on adaptive threshold and optimized weighted median filter, Biomed. Signal Proces., 75, 103552, https://doi.org/10.1016/j.bspc.2022.103552, 2022.
Haarig, M., Ansmann, A., Gasteiger, J., Kandler, K., Althausen, D., Baars, H., Radenz, M., and Farrell, D. A.: Dry versus wet marine particle optical properties: RH dependence of depolarization ratio, backscatter, and extinction from multiwavelength lidar measurements during SALTRACE, Atmos. Chem. Phys., 17, 14199–14217, https://doi.org/10.5194/acp-17-14199-2017, 2017a.
Haarig, M., Ansmann, A., Althausen, D., Klepel, A., Groß, S., Freudenthaler, V., Toledano, C., Mamouri, R.-E., Farrell, D. A., Prescod, D. A., Marinou, E., Burton, S. P., Gasteiger, J., Engelmann, R., and Baars, H.: Triple-wavelength depolarization-ratio profiling of Saharan dust over Barbados during SALTRACE in 2013 and 2014, Atmos. Chem. Phys., 17, 10767–10794, https://doi.org/10.5194/acp-17-10767-2017, 2017b.
Haarig, M., Ansmann, A., Baars, H., Jimenez, C., Veselovskii, I., Engelmann, R., and Althausen, D.: Depolarization and lidar ratios at 355, 532, and 1064 nm and microphysical properties of aged tropospheric and stratospheric Canadian wildfire smoke, Atmos. Chem. Phys., 18, 11847–11861, https://doi.org/10.5194/acp-18-11847-2018, 2018.
Hair, J. W., Hostetler, C. A., Cook, A. L., Harper, D. B., Ferrare, R. A., Mack, T. L., Welch, W., Izquierdo, L. R., and Hovis, F. E.: Airborne High Spectral Resolution Lidar for profiling Aerosol optical properties, Appl. Opt., 47, 6734–6752, https://doi.org/10.1364/AO.47.006734, 2008.
Hara, K., Osada, K., and Yamanouchi, T.: Tethered balloon-borne aerosol measurements: seasonal and vertical variations of aerosol constituents over Syowa Station, Antarctica, Atmos. Chem. Phys., 13, 9119–9139, https://doi.org/10.5194/acp-13-9119-2013, 2013.
Harvey, N. J., Hogan, R. J., and Dacre, H. F.: A method to diagnose boundary-layer type using doppler lidar, Q. J. Roy. Meteor. Soc., 139, 1681–1693, https://doi.org/10.1002/qj.2068, 2013.
Hirsikko, A., O'Connor, E. J., Komppula, M., Korhonen, K., Pfüller, A., Giannakaki, E., Wood, C. R., Bauer-Pfundstein, M., Poikonen, A., Karppinen, T., Lonka, H., Kurri, M., Heinonen, J., Moisseev, D., Asmi, E., Aaltonen, V., Nordbo, A., Rodriguez, E., Lihavainen, H., Laaksonen, A., Lehtinen, K. E. J., Laurila, T., Petäjä, T., Kulmala, M., and Viisanen, Y.: Observing wind, aerosol particles, cloud and precipitation: Finland's new ground-based remote-sensing network, Atmos. Meas. Tech., 7, 1351–1375, https://doi.org/10.5194/amt-7-1351-2014, 2014.
Hirtl, M., Arnold, D., Baro, R., Brenot, H., Coltelli, M., Eschbacher, K., Hard-Stremayer, H., Lipok, F., Maurer, C., Meinhard, D., Mona, L., Mulder, M. D., Papagiannopoulos, N., Pernsteiner, M., Plu, M., Robertson, L., Rokitansky, C.-H., Scherllin-Pirscher, B., Sievers, K., Sofiev, M., Som de Cerff, W., Steinheimer, M., Stuefer, M., Theys, N., Uppstu, A., Wagenaar, S., Winkler, R., Wotawa, G., Zobl, F., and Zopp, R.: A volcanic-hazard demonstration exercise to assess and mitigate the impacts of volcanic ash clouds on civil and military aviation, Nat. Hazards Earth Syst. Sci., 20, 1719–1739, https://doi.org/10.5194/nhess-20-1719-2020, 2020.
Hu, Y., Liu, Z., Winker, D., Vaughan, M., Noel, V., Bissonnette, L., Roy, G., and McGill, M.: Simple relation between lidar multiple scattering and depolarization for water clouds, Opt. Lett., 31, 1809, https://doi.org/10.1364/ol.31.001809, 2006.
Hughes, D. D., Mampage, C. B. A., Jones, L. M., Liu, Z., and Stone, E. A.: Characterization of Atmospheric Pollen Fragments during Springtime Thunderstorms, Environmental Science and Technology Letters, 7, 409–414, https://doi.org/10.1021/acs.estlett.0c00213, 2020.
Illingworth, A. J., Hogan, R. J., O'Connor, E. J., Bouniol, D., Brooks, M. E., Delanoë, J., Donovan, D. P., Eastment, J. D., Gaussiat, N., Goddard, J. W. F., Haeffelin, M., Klein Baltinik, H., Krasnov, O. A., Pelon, J., Piriou, J. M., Protat, A., Russchenberg, H. W. J., Seifert, A., Tompkins, A. M., van Zadelhoff, G. J., Vinit, F., Willen, U., Wilson, D. R., and Wrench, C. L.: Cloudnet: Continuous evaluation of cloud profiles in seven operational models using ground-based observations, B. Am. Meteorol. Soc., 88, 883–898, https://doi.org/10.1175/BAMS-88-6-883, 2007.
Illingworth, A. J., Barker, H. W., Beljaars, A., Ceccaldi, M., Chepfer, H., Clerbaux, N., Cole, J., Delanoë, J., Domenech, C., Donovan, D. P., Fukuda, S., Hirakata, M., Hogan, R. J., Huenerbein, A., Kollias, P., Kubota, T., Nakajima, T., Nakajima, T. Y., Nishizawa, T., Ohno, Y., Okamoto, H., Oki, R., Sato, K., Satoh, M., Shephard, M. W., Velázquez-Blázquez, A., Wandinger, U., Wehr, T., and Van Zadelhoff, G. J.: The earthcare satellite: The next step forward in global measurements of clouds, aerosols, precipitation, and radiation, B. Am. Meteorol. Soc., 96, 1311–1332, https://doi.org/10.1175/BAMS-D-12-00227.1, 2015.
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896, 2021.
Jato, M. V., Rodríguez, F. J., and Seijo, M. C.: Pinus pollen in the atmosphere of Vigo and its relationship to meteorological factors, Int. J. Biometeorol., 43, 147–153, https://doi.org/10.1007/s004840050001, 2000.
Johnson, B. T., Osborne, S. R., Haywood, J. M., and Harrison, M. A. J.: Aircraft measurements of biomass burning aerosol over West Africa during DABEX, J. Geophys. Res.-Atmos., 113, D00C06, https://doi.org/10.1029/2007JD009451, 2008.
Johnson, J. B.: Thermal Agitation of Electricity in Conductors, Phys. Rev., 32, 97–109, https://doi.org/10.1103/PhysRev.32.97, 1928.
Kanawade, V. P., Srivastava, A. K., Ram, K., Asmi, E., Vakkari, V., Soni, V. K., Varaprasad, V., and Sarangi, C.: What caused severe air pollution episode of November 2016 in New Delhi?, Atmos. Environ., 222, 117125, https://doi.org/10.1016/j.atmosenv.2019.117125, 2020.
Käpylä, M.: Diurnal variation of tree pollen in the air in Finland, Grana, 23, 167–176, https://doi.org/10.1080/00173138409427712, 1984.
Katifori, E., Alben, S., Cerda, E., Nelson, D. R., and Dumais, J.: Foldable structures and the natural design of pollen grains, P. Natl. Acad. Sci. USA, 107, 7635–7639, https://doi.org/10.1073/pnas.0911223107, 2010.
Koivikko, A., Kupias, R., Mäkinen, Y., and Pohjola, A.: Pollen Seasons: Forecasts of the Most Important Allergenic Plants in Finland, Allergy, 41, 233–242, https://doi.org/10.1111/j.1398-9995.1986.tb02023.x, 1986.
Latorre, F. and Caccavari, M. A.: Airborne pollen patterns in Mar del Plata atmosphere (Argentina) and its relationship with meteorological conditions, Aerobiologia, 25, 297–312, https://doi.org/10.1007/s10453-009-9134-6, 2009.
Le, V., Lobo, H., O'Connor, E., and Vakkari, V.: Data and code for “Long-term aerosol particle depolarization ratio measurements with Halo Doppler lidar” by Viet Le et al. (2023), Finnish Meteorological Institute [data set], https://doi.org/10.57707/FMI-B2SHARE.F82603E69CEA49B888F94D0E8A85E787, 2023.
Li, S., Kang, X., and Hu, J.: Image fusion with guided filtering, IEEE T. Image Process., 22, 2864–2875, https://doi.org/10.1109/TIP.2013.2244222, 2013.
Liou, K.-N. and Schotland, R. M.: Multiple Backscattering and Depolarization from Water Clouds for a Pulsed Lidar System, J. Atmos. Sci., 28, 772–784, https://doi.org/10.1175/1520-0469(1971)028<0772:mbadfw>2.0.co;2, 1971.
Luoma, K., Virkkula, A., Aalto, P., Petäjä, T., and Kulmala, M.: Over a 10-year record of aerosol optical properties at SMEAR II, Atmos. Chem. Phys., 19, 11363–11382, https://doi.org/10.5194/acp-19-11363-2019, 2019.
Mamali, D., Marinou, E., Sciare, J., Pikridas, M., Kokkalis, P., Kottas, M., Binietoglou, I., Tsekeri, A., Keleshis, C., Engelmann, R., Baars, H., Ansmann, A., Amiridis, V., Russchenberg, H., and Biskos, G.: Vertical profiles of aerosol mass concentration derived by unmanned airborne in situ and remote sensing instruments during dust events, Atmos. Meas. Tech., 11, 2897–2910, https://doi.org/10.5194/amt-11-2897-2018, 2018.
Mamouri, R.-E. and Ansmann, A.: Potential of polarization lidar to provide profiles of CCN- and INP-relevant aerosol parameters, Atmos. Chem. Phys., 16, 5905–5931, https://doi.org/10.5194/acp-16-5905-2016, 2016.
Manninen, A. J., O'Connor, E. J., Vakkari, V., and Petäjä, T.: A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland, Atmos. Meas. Tech., 9, 817–827, https://doi.org/10.5194/amt-9-817-2016, 2016.
Manninen, H. E., Sihto-Nissilä, S. L., Hiltunen, V., Aalto, P. P., Kulmala, M., Petäjä, T., Manninen, H. E., Bäck, J., Hari, P., Huffman, J. A., Huffman, J. A., Saarto, A., Pessi, A. M., and Hidalgo, P. J.: Patterns in airborne pollen and other primary biological aerosol particles (PBAP), and their contribution to aerosol mass and number in a boreal forest, Boreal Environ. Res., 19, 383–405, http://hdl.handle.net/10138/228775 (last access: 17 January 2024), 2014.
Miguel, A. G., Taylor, P. E., House, J., Glovsky, M. M., and Flagan, R. C.: Meteorological Influences on Respirable Fragment Release from Chinese Elm Pollen, Aerosol Sci. Tech., 40, 690–696, https://doi.org/10.1080/02786820600798869, 2006.
Moisseev, D., O'Connor, E., and Petäjä, T.: Custom collection of Cloudnet classification data from Hyytiälä between 26 Nov 2016 and 31 Dec 2019, ACTRIS Cloud remote sensing data centre unit (CLU) [data set], https://doi.org/10.60656/919d6e2a0e454c18, 2023.
Morcrette, J.-J., Boucher, O., Jones, L., Salmond, D., Bechtold, P., Beljaars, A., Benedetti, A., Bonet, A., Kaiser, J. W., Razinger, M., Schulz, M., Serrar, S., Simmons, A. J., Sofiev, M., Suttie, M., Tompkins, A. M., and Untch, A.: Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: Forward modeling, J. Geophys. Res.-Atmos., 114, D06206, https://doi.org/10.1029/2008JD011235, 2009.
Müller, D., Ansmann, A., Mattis, I., Tesche, M., Wandinger, U., Althausen, D., and Pisani, G.: Aerosol-type-dependent lidar ratios observed with Raman lidar, J. Geophys. Res.-Atmos., 112, D16202, https://doi.org/10.1029/2006JD008292, 2007.
Murayama, T., Sugimoto, N., Uno, I., Kinoshita, K., Aoki, K., Hagiwara, N., Liu, Z., Matsui, I., Sakai, T., Shibata, T., Arao, K., Sohn, B. J., Won, J. G., Yoon, S. C., Li, T., Zhou, J., Hu, H., Abo, M., Iokibe, K., Koga, R., and Iwasaka, Y.: Ground-based network observation of Asian dust events of April 1998 in east Asia, J. Geophys. Res.-Atmos., 106, 18345–18359, https://doi.org/10.1029/2000JD900554, 2001.
Mylonaki, M., Papayannis, A., Papanikolaou, C. A., Foskinis, R., Soupiona, O., Maroufidis, G., Anagnou, D., and Kralli, E.: Tropospheric vertical profiling of the aerosol backscatter coefficient and the particle linear depolarization ratio for different aerosol mixtures during the PANACEA campaign in July 2019 at Volos, Greece, Atmos. Environ., 247, 118184, https://doi.org/10.1016/j.atmosenv.2021.118184, 2021.
Noh, Y. M., Müller, D., Lee, H., and Choi, T. J.: Influence of biogenic pollen on optical properties of atmospheric aerosols observed by lidar over Gwangju, South Korea, Atmos. Environ., 69, 139–147, https://doi.org/10.1016/j.atmosenv.2012.12.018, 2013a.
Noh, Y. M., Lee, H., Mueller, D., Lee, K., Shin, D., Shin, S., Choi, T. J., Choi, Y. J., and Kim, K. R.: Investigation of the diurnal pattern of the vertical distribution of pollen in the lower troposphere using LIDAR, Atmos. Chem. Phys., 13, 7619–7629, https://doi.org/10.5194/acp-13-7619-2013, 2013b.
Nyquist, H.: Thermal Agitation of Electric Charge in Conductors, Phys. Rev., 32, 110–113, https://doi.org/10.1103/PhysRev.32.110, 1928.
O'Connor, E. J., Illingworth, A. J., and Hogan, R. J.: A technique for autocalibration of cloud lidar, J. Atmos. Ocean. Tech., 21, https://doi.org/10.1175/1520-0426(2004)021<0777:ATFAOC>2.0.CO;2, 2004.
Ohneiser, K., Ansmann, A., Baars, H., Seifert, P., Barja, B., Jimenez, C., Radenz, M., Teisseire, A., Floutsi, A., Haarig, M., Foth, A., Chudnovsky, A., Engelmann, R., Zamorano, F., Bühl, J., and Wandinger, U.: Smoke of extreme Australian bushfires observed in the stratosphere over Punta Arenas, Chile, in January 2020: optical thickness, lidar ratios, and depolarization ratios at 355 and 532 nm, Atmos. Chem. Phys., 20, 8003–8015, https://doi.org/10.5194/acp-20-8003-2020, 2020.
Oikonen, M. K., Hicks, S., Heino, S., and Rantio-Lehtimäki, A.: The start of the birch pollen season in Finnish Lapland: Separating non-local from local birch pollen and the implication for allergy sufferers, Grana, 44, 181–186, https://doi.org/10.1080/00173130510010602, 2005.
Pappalardo, G., Amodeo, A., Apituley, A., Comeron, A., Freudenthaler, V., Linné, H., Ansmann, A., Bösenberg, J., D'Amico, G., Mattis, I., Mona, L., Wandinger, U., Amiridis, V., Alados-Arboledas, L., Nicolae, D., and Wiegner, M.: EARLINET: towards an advanced sustainable European aerosol lidar network, Atmos. Meas. Tech., 7, 2389–2409, https://doi.org/10.5194/amt-7-2389-2014, 2014.
Pearson, G., Davies, F., and Collier, C.: An analysis of the performance of the UFAM pulsed Doppler lidar for observing the boundary layer, J. Atmos. Ocean. Tech., 26, 240–250, https://doi.org/10.1175/2008JTECHA1128.1, 2009.
Pentikäinen, P., O'Connor, E. J., Manninen, A. J., and Ortiz-Amezcua, P.: Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar, Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020, 2020.
Perreault, S. and Hébert, P.: Median filtering in constant time, IEEE T. Image Process., 16, 2389–2394, https://doi.org/10.1109/TIP.2007.902329, 2007.
Petäjä, T., Laakso, L., Grönholm, T., Launiainen, S., Evele-Peltoniemi, I., Virkkula, A., Leskinen, A., Backman, J., Manninen, H. E., Sipilä, M., Haapanala, S., Hämeri, K., Vanhala, E., Tuomi, T., Paatero, J., Aurela, M., Hakola, H., Makkonen, U., Hellén, H., Hillamo, R., Vira, J., Prank, M., Sofiev, M., Siitari-Kauppi, M., Laaksonen, A., lehtinen, K. E. J., Kulmala, M., Viisanen, Y., and Kerminen, V.-M.: In-situ observations of Eyjafjallajökull ash particles by hot-air balloon, Atmos. Environ., 48, 104–112, https://doi.org/10.1016/j.atmosenv.2011.08.046, 2012.
Pisso, I., Sollum, E., Grythe, H., Kristiansen, N. I., Cassiani, M., Eckhardt, S., Arnold, D., Morton, D., Thompson, R. L., Groot Zwaaftink, C. D., Evangeliou, N., Sodemann, H., Haimberger, L., Henne, S., Brunner, D., Burkhart, J. F., Fouilloux, A., Brioude, J., Philipp, A., Seibert, P., and Stohl, A.: The Lagrangian particle dispersion model FLEXPART version 10.4, Geosci. Model Dev., 12, 4955–4997, https://doi.org/10.5194/gmd-12-4955-2019, 2019.
Pratt, K. A. and Prather, K. A.: Aircraft measurements of vertical profiles of aerosol mixing states, J. Geophys. Res.-Atmos., 115, D11305, https://doi.org/10.1029/2009JD013150, 2010.
Rankin, A. M. and Wolff, E. W.: Aerosol profiling using a tethered balloon in coastal Antarctica, J. Atmos. Ocean. Tech., 19, 1978–1985, https://doi.org/10.1175/1520-0426(2002)019<1978:APUATB>2.0.CO;2, 2002.
Rauber, R. M. and Nesbitt, S. W.: Radar meteorology: A first course, John Wiley & Sons Ltd, 461 pp., ISBN 9781118432624, 2018.
Rosati, B., Herrmann, E., Bucci, S., Fierli, F., Cairo, F., Gysel, M., Tillmann, R., Größ, J., Gobbi, G. P., Di Liberto, L., Di Donfrancesco, G., Wiedensohler, A., Weingartner, E., Virtanen, A., Mentel, T. F., and Baltensperger, U.: Studying the vertical aerosol extinction coefficient by comparing in situ airborne data and elastic backscatter lidar, Atmos. Chem. Phys., 16, 4539–4554, https://doi.org/10.5194/acp-16-4539-2016, 2016.
Rousseau, D. D., Duzer, D., Cambon, G., Jolly, D., Poulsen, U., Ferrier, J., Schevin, P., and Gros, R.: Long distance transport of pollen to Greenland, Geophys. Res. Lett., 30, 1765, https://doi.org/10.1029/2003GL017539, 2003.
Rousseau, D. D., Schevin, P., Duzer, D., Cambon, G., Ferrier, J., Jolly, D., and Poulsen, U.: New evidence of long distance pollen transport to southern Greenland in late spring, Rev. Palaeobot. Palyno., 141, 277–286, https://doi.org/10.1016/j.revpalbo.2006.05.001, 2006.
Sassen, K.: Indirect climate forcing over the western US from Asian dust storms, Geophys. Res. Lett., 29, 103-1–103-4, https://doi.org/10.1029/2001gl014051, 2002.
Seibert, P. and Frank, A.: Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode, Atmos. Chem. Phys., 4, 51–63, https://doi.org/10.5194/acp-4-51-2004, 2004.
Shang, X., Giannakaki, E., Bohlmann, S., Filioglou, M., Saarto, A., Ruuskanen, A., Leskinen, A., Romakkaniemi, S., and Komppula, M.: Optical characterization of pure pollen types using a multi-wavelength Raman polarization lidar, Atmos. Chem. Phys., 20, 15323–15339, https://doi.org/10.5194/acp-20-15323-2020, 2020.
Skjøth, C. A., Sommer, J., Stach, A., Smith, M., and Brandt, J.: The long-range transport of birch (Betula) pollen from Poland and Germany causes significant pre-season concentrations in Denmark, Clin. Exp. Allergy, 37, 1204–1212, https://doi.org/10.1111/j.1365-2222.2007.02771.x, 2007.
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem. Phys., 5, 2461–2474, https://doi.org/10.5194/acp-5-2461-2005, 2005.
Szczepanek, K., Myszkowska, D., Worobiec, E., Piotrowicz, K., Ziemianin, M., and Bielec-Bąkowska, Z.: The long-range transport of Pinaceae pollen: an example in Kraków (southern Poland), Aerobiologia, 33, 109–125, https://doi.org/10.1007/s10453-016-9454-2, 2017.
Taylor, P. E., Flagan, R. C., Valenta, R., and Glovsky, M. M.: Release of allergens as respirable aerosols: A link between grass pollen and asthma, J. Allergy Clin. Immun., 109, 51–56, https://doi.org/10.1067/mai.2002.120759, 2002.
Taylor, P. E., Flagan, R. C., Miguel, A. G., Valenta, R., and Glovsky, M. M.: Birch pollen rupture and the release of aerosols of respirable allergens, Clin. Exp. Allergy, 34, 1591–1596, https://doi.org/10.1111/j.1365-2222.2004.02078.x, 2004.
Tukiainen, S., O'Connor, E., and Korpinen, A.: CloudnetPy: A Python package for processing cloud remote sensing data, Journal of Open Source Software, 5, 2123, https://doi.org/10.21105/joss.02123, 2020.
Tuononen, M., O'Connor, E. J., and Sinclair, V. A.: Evaluating solar radiation forecast uncertainty, Atmos. Chem. Phys., 19, 1985–2000, https://doi.org/10.5194/acp-19-1985-2019, 2019.
Vakkari, V., Manninen, A. J., O'Connor, E. J., Schween, J. H., van Zyl, P. G., and Marinou, E.: A novel post-processing algorithm for Halo Doppler lidars, Atmos. Meas. Tech., 12, 839–852, https://doi.org/10.5194/amt-12-839-2019, 2019.
Vakkari, V., Baars, H., Bohlmann, S., Bühl, J., Komppula, M., Mamouri, R.-E., and O'Connor, E. J.: Aerosol particle depolarization ratio at 1565 nm measured with a Halo Doppler lidar, Atmos. Chem. Phys., 21, 5807–5820, https://doi.org/10.5194/acp-21-5807-2021, 2021.
Vázquez, L. M., Galán, C., and Domínguez-Vilches, E.: Influence of meteorological parameters on olea pollen concentrations in Córdoba (South-western Spain), Int. J. Biometeorol., 48, 83–90, https://doi.org/10.1007/s00484-003-0187-x, 2003.
Wang, Y., Yu, M., Wang, Y., Tang, G., Song, T., Zhou, P., Liu, Z., Hu, B., Ji, D., Wang, L., Zhu, X., Yan, C., Ehn, M., Gao, W., Pan, Y., Xin, J., Sun, Y., Kerminen, V.-M., Kulmala, M., and Petäjä, T.: Rapid formation of intense haze episodes via aerosol–boundary layer feedback in Beijing, Atmos. Chem. Phys., 20, 45–53, https://doi.org/10.5194/acp-20-45-2020, 2020.
Weitkamp, C.: Lidar: range-resolved optical remote sensing of the atmosphere, Springer-Verlag, New York, 455 pp., ISBN 978-0-387-40075-4, 2005.
Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., Hunt, W. H., and Young, S. A.: Overview of the CALIPSO mission and CALIOP data processing algorithms, J. Atmos. Ocean. Tech., 26, 2310–2323, https://doi.org/10.1175/2009JTECHA1281.1, 2009.
Wise, M. E., Semeniuk, T. A., Bruintjes, R., Martin, S. T., Russell, L. M., and Buseck, P. R.: Hygroscopic behavior of NaCl-bearing natural aerosol particles using environmental transmission electron microscopy, J. Geophys. Res.-Atmos., 112, D10224, https://doi.org/10.1029/2006JD007678, 2007.
Zhao, C., Wang, Y., Wang, Q., Li, Z., Wang, Z., and Liu, D.: A new cloud and aerosol layer detection method based on micropulse lidar measurements, J. Geophys. Res., 119, 6788–6802, https://doi.org/10.1002/2014JD021760, 2014.
Executive editor
This is the first time showing that long-term polarization observations with a Doppler lidar are possible. Second, the methodology could be applied to other HALO lidars and thus expand the capabilities for observing atmospheric aerosol. Third: It shows that Finland (any maybe whole Scandinavia) is during summer time most of the time dominated by Pollen or other biogenic aerosol, something which is maybe attributed to the continental background class used in CALIPSO, and not yet fully understood.
This is the first time showing that long-term polarization observations with a Doppler lidar are...
Short summary
This study offers a long-term overview of aerosol particle depolarization ratio at the wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during 4 years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio such as the detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
This study offers a long-term overview of aerosol particle depolarization ratio at the...