Articles | Volume 14, issue 6
Atmos. Meas. Tech., 14, 4565–4574, 2021
https://doi.org/10.5194/amt-14-4565-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue: Tropospheric profiling (ISTP11) (AMT/ACP inter-journal SI)
Research article
21 Jun 2021
Research article
| 21 Jun 2021
Evaluation of micro rain radar-based precipitation classification algorithms to discriminate between stratiform and convective precipitation
Andreas Foth et al.
Related authors
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-149, https://doi.org/10.5194/amt-2022-149, 2022
Preprint under review for AMT
Short summary
Short summary
This study demonstrates that the VOODOO method could be a powerful addition to the existing Cloudnet target classification, making the detection of liquid layers beyond complete lidar attenuation possible. In conclusion, VOODOO performs best for (multi-layer) stratiform, deep mixed-phase cloud situations with liquid water path >100g m-2.
Albert Ansmann, Kevin Ohneiser, Rodanthi-Elisavet Mamouri, Daniel A. Knopf, Igor Veselovskii, Holger Baars, Ronny Engelmann, Andreas Foth, Cristofer Jimenez, Patric Seifert, and Boris Barja
Atmos. Chem. Phys., 21, 9779–9807, https://doi.org/10.5194/acp-21-9779-2021, https://doi.org/10.5194/acp-21-9779-2021, 2021
Short summary
Short summary
We present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area concentration of wildfire smoke layers, and related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations. The new analysis scheme is applied to ground-based lidar observations of stratospheric Australian smoke over southern South America and to spaceborne lidar observations of tropospheric North American smoke.
Kevin Ohneiser, Albert Ansmann, Holger Baars, Patric Seifert, Boris Barja, Cristofer Jimenez, Martin Radenz, Audrey Teisseire, Athina Floutsi, Moritz Haarig, Andreas Foth, Alexandra Chudnovsky, Ronny Engelmann, Félix Zamorano, Johannes Bühl, and Ulla Wandinger
Atmos. Chem. Phys., 20, 8003–8015, https://doi.org/10.5194/acp-20-8003-2020, https://doi.org/10.5194/acp-20-8003-2020, 2020
Short summary
Short summary
Unique lidar observations of a strong perturbation in stratospheric aerosol conditions in the Southern Hemisphere caused by the extreme Australian bushfires in 2019–2020 are presented. One of the main goals of this article is to provide the CALIPSO and Aeolus spaceborne lidar science teams with basic input parameters (lidar ratios, depolarization ratios) for a trustworthy documentation of this record-breaking event.
Andreas Foth, Thomas Kanitz, Ronny Engelmann, Holger Baars, Martin Radenz, Patric Seifert, Boris Barja, Michael Fromm, Heike Kalesse, and Albert Ansmann
Atmos. Chem. Phys., 19, 6217–6233, https://doi.org/10.5194/acp-19-6217-2019, https://doi.org/10.5194/acp-19-6217-2019, 2019
Short summary
Short summary
In this study, we present the vertical aerosol distribution in the pristine region of the southern tip of South America determined by ground-based and spaceborne lidar observations. Most aerosol load is contained within the planetary boundary layer up to about 1200 m. The free troposphere is characterized by a very low aerosol concentration but a frequent occurrence of clouds. Lofted aerosol layers were rarely observed and, when present, were characterized by very low optical thicknesses.
Andreas Foth and Bernhard Pospichal
Atmos. Meas. Tech., 10, 3325–3344, https://doi.org/10.5194/amt-10-3325-2017, https://doi.org/10.5194/amt-10-3325-2017, 2017
Short summary
Short summary
We present a two-step retrieval that provides a continuous time series of water vapour profiles from ground-based remote sensing in a straightforward way to offer a broad application. The retrieval combines the Raman lidar mass mixing ratio and the microwave radiometer brightness temperature. Its application results in reliable water vapour profiles and error estimates also from within and above a cloud during all non-precipitating conditions.
Andreas Macke, Patric Seifert, Holger Baars, Christian Barthlott, Christoph Beekmans, Andreas Behrendt, Birger Bohn, Matthias Brueck, Johannes Bühl, Susanne Crewell, Thomas Damian, Hartwig Deneke, Sebastian Düsing, Andreas Foth, Paolo Di Girolamo, Eva Hammann, Rieke Heinze, Anne Hirsikko, John Kalisch, Norbert Kalthoff, Stefan Kinne, Martin Kohler, Ulrich Löhnert, Bomidi Lakshmi Madhavan, Vera Maurer, Shravan Kumar Muppa, Jan Schween, Ilya Serikov, Holger Siebert, Clemens Simmer, Florian Späth, Sandra Steinke, Katja Träumner, Silke Trömel, Birgit Wehner, Andreas Wieser, Volker Wulfmeyer, and Xinxin Xie
Atmos. Chem. Phys., 17, 4887–4914, https://doi.org/10.5194/acp-17-4887-2017, https://doi.org/10.5194/acp-17-4887-2017, 2017
Short summary
Short summary
This article provides an overview of the instrumental setup and the main results obtained during the two HD(CP)2 Observational Prototype Experiments HOPE-Jülich and HOPE-Melpitz conducted in Germany in April–May and Sept 2013, respectively. Goal of the field experiments was to provide high-resolution observational datasets for both, improving the understaning of boundary layer and cloud processes, as well as for the evaluation of the new ICON model that is run at 156 m horizontal resolution.
Holger Baars, Thomas Kanitz, Ronny Engelmann, Dietrich Althausen, Birgit Heese, Mika Komppula, Jana Preißler, Matthias Tesche, Albert Ansmann, Ulla Wandinger, Jae-Hyun Lim, Joon Young Ahn, Iwona S. Stachlewska, Vassilis Amiridis, Eleni Marinou, Patric Seifert, Julian Hofer, Annett Skupin, Florian Schneider, Stephanie Bohlmann, Andreas Foth, Sebastian Bley, Anne Pfüller, Eleni Giannakaki, Heikki Lihavainen, Yrjö Viisanen, Rakesh Kumar Hooda, Sérgio Nepomuceno Pereira, Daniele Bortoli, Frank Wagner, Ina Mattis, Lucja Janicka, Krzysztof M. Markowicz, Peggy Achtert, Paulo Artaxo, Theotonio Pauliquevis, Rodrigo A. F. Souza, Ved Prakesh Sharma, Pieter Gideon van Zyl, Johan Paul Beukes, Junying Sun, Erich G. Rohwer, Ruru Deng, Rodanthi-Elisavet Mamouri, and Felix Zamorano
Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016, https://doi.org/10.5194/acp-16-5111-2016, 2016
Short summary
Short summary
The findings from more than 10 years of global aerosol lidar measurements with Polly systems are summarized, and a data set of optical properties for specific aerosol types is given. An automated data retrieval algorithm for continuous Polly lidar observations is presented and discussed by means of a Saharan dust advection event in Leipzig, Germany. Finally, a statistic on the vertical aerosol distribution including the seasonal variability at PollyNET locations around the globe is presented.
A. Foth, H. Baars, P. Di Girolamo, and B. Pospichal
Atmos. Chem. Phys., 15, 7753–7763, https://doi.org/10.5194/acp-15-7753-2015, https://doi.org/10.5194/acp-15-7753-2015, 2015
Short summary
Short summary
We present a method to derive water vapour profiles from Raman lidar measurements calibrated by the integrated water vapour from a collocated microwave radiometer. These simultaneous observations provide an operational and continuous measurement of water vapour profiles. The stability of the calibration factor allows for the calibration of the lidar even in the presence of clouds. Based on this approach, water vapour profiles can be retrieved during all non-precipitating conditions.
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-149, https://doi.org/10.5194/amt-2022-149, 2022
Preprint under review for AMT
Short summary
Short summary
This study demonstrates that the VOODOO method could be a powerful addition to the existing Cloudnet target classification, making the detection of liquid layers beyond complete lidar attenuation possible. In conclusion, VOODOO performs best for (multi-layer) stratiform, deep mixed-phase cloud situations with liquid water path >100g m-2.
Teresa Vogl, Maximilian Maahn, Stefan Kneifel, Willi Schimmel, Dmitri Moisseev, and Heike Kalesse-Los
Atmos. Meas. Tech., 15, 365–381, https://doi.org/10.5194/amt-15-365-2022, https://doi.org/10.5194/amt-15-365-2022, 2022
Short summary
Short summary
We are using machine learning techniques, a type of artificial intelligence, to detect graupel formation in clouds. The measurements used as input to the machine learning framework were performed by cloud radars. Cloud radars are instruments located at the ground, emitting radiation with wavelenghts of a few millimeters vertically into the cloud and measuring the back-scattered signal. Our novel technique can be applied to different radar systems and different weather conditions.
Heike Kalesse-Los, Willi Schimmel, Edward Luke, and Patric Seifert
Atmos. Meas. Tech., 15, 279–295, https://doi.org/10.5194/amt-15-279-2022, https://doi.org/10.5194/amt-15-279-2022, 2022
Short summary
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It is important to detect the vertical distribution of cloud droplets and ice in mixed-phase clouds. Here, an artificial neural network (ANN) previously developed for Arctic clouds is applied to a mid-latitudinal cloud radar data set. The performance of this technique is contrasted to the Cloudnet target classification. For thick/multi-layer clouds, the machine learning technique is better at detecting liquid than Cloudnet, but if lidar data are available Cloudnet is at least as good as the ANN.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
Short summary
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Albert Ansmann, Kevin Ohneiser, Rodanthi-Elisavet Mamouri, Daniel A. Knopf, Igor Veselovskii, Holger Baars, Ronny Engelmann, Andreas Foth, Cristofer Jimenez, Patric Seifert, and Boris Barja
Atmos. Chem. Phys., 21, 9779–9807, https://doi.org/10.5194/acp-21-9779-2021, https://doi.org/10.5194/acp-21-9779-2021, 2021
Short summary
Short summary
We present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area concentration of wildfire smoke layers, and related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations. The new analysis scheme is applied to ground-based lidar observations of stratospheric Australian smoke over southern South America and to spaceborne lidar observations of tropospheric North American smoke.
Kevin Ohneiser, Albert Ansmann, Holger Baars, Patric Seifert, Boris Barja, Cristofer Jimenez, Martin Radenz, Audrey Teisseire, Athina Floutsi, Moritz Haarig, Andreas Foth, Alexandra Chudnovsky, Ronny Engelmann, Félix Zamorano, Johannes Bühl, and Ulla Wandinger
Atmos. Chem. Phys., 20, 8003–8015, https://doi.org/10.5194/acp-20-8003-2020, https://doi.org/10.5194/acp-20-8003-2020, 2020
Short summary
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Unique lidar observations of a strong perturbation in stratospheric aerosol conditions in the Southern Hemisphere caused by the extreme Australian bushfires in 2019–2020 are presented. One of the main goals of this article is to provide the CALIPSO and Aeolus spaceborne lidar science teams with basic input parameters (lidar ratios, depolarization ratios) for a trustworthy documentation of this record-breaking event.
Heike Kalesse, Teresa Vogl, Cosmin Paduraru, and Edward Luke
Atmos. Meas. Tech., 12, 4591–4617, https://doi.org/10.5194/amt-12-4591-2019, https://doi.org/10.5194/amt-12-4591-2019, 2019
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In a cloud, different particles like liquid water droplets and ice particles can exist simultaneously. To study the evolution of cloud particles from cloud top to bottom one has to find out how many different types of particles with different fall velocities are present. This can be done by analyzing the number of peaks in upward-looking cloud radar Doppler spectra. A new machine-learning algorithm (named PEAKO) that determines the number of peaks is introduced and compared to existing methods.
Andreas Foth, Thomas Kanitz, Ronny Engelmann, Holger Baars, Martin Radenz, Patric Seifert, Boris Barja, Michael Fromm, Heike Kalesse, and Albert Ansmann
Atmos. Chem. Phys., 19, 6217–6233, https://doi.org/10.5194/acp-19-6217-2019, https://doi.org/10.5194/acp-19-6217-2019, 2019
Short summary
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In this study, we present the vertical aerosol distribution in the pristine region of the southern tip of South America determined by ground-based and spaceborne lidar observations. Most aerosol load is contained within the planetary boundary layer up to about 1200 m. The free troposphere is characterized by a very low aerosol concentration but a frequent occurrence of clouds. Lofted aerosol layers were rarely observed and, when present, were characterized by very low optical thicknesses.
Andreas Foth and Bernhard Pospichal
Atmos. Meas. Tech., 10, 3325–3344, https://doi.org/10.5194/amt-10-3325-2017, https://doi.org/10.5194/amt-10-3325-2017, 2017
Short summary
Short summary
We present a two-step retrieval that provides a continuous time series of water vapour profiles from ground-based remote sensing in a straightforward way to offer a broad application. The retrieval combines the Raman lidar mass mixing ratio and the microwave radiometer brightness temperature. Its application results in reliable water vapour profiles and error estimates also from within and above a cloud during all non-precipitating conditions.
Andreas Macke, Patric Seifert, Holger Baars, Christian Barthlott, Christoph Beekmans, Andreas Behrendt, Birger Bohn, Matthias Brueck, Johannes Bühl, Susanne Crewell, Thomas Damian, Hartwig Deneke, Sebastian Düsing, Andreas Foth, Paolo Di Girolamo, Eva Hammann, Rieke Heinze, Anne Hirsikko, John Kalisch, Norbert Kalthoff, Stefan Kinne, Martin Kohler, Ulrich Löhnert, Bomidi Lakshmi Madhavan, Vera Maurer, Shravan Kumar Muppa, Jan Schween, Ilya Serikov, Holger Siebert, Clemens Simmer, Florian Späth, Sandra Steinke, Katja Träumner, Silke Trömel, Birgit Wehner, Andreas Wieser, Volker Wulfmeyer, and Xinxin Xie
Atmos. Chem. Phys., 17, 4887–4914, https://doi.org/10.5194/acp-17-4887-2017, https://doi.org/10.5194/acp-17-4887-2017, 2017
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This article provides an overview of the instrumental setup and the main results obtained during the two HD(CP)2 Observational Prototype Experiments HOPE-Jülich and HOPE-Melpitz conducted in Germany in April–May and Sept 2013, respectively. Goal of the field experiments was to provide high-resolution observational datasets for both, improving the understaning of boundary layer and cloud processes, as well as for the evaluation of the new ICON model that is run at 156 m horizontal resolution.
Holger Baars, Thomas Kanitz, Ronny Engelmann, Dietrich Althausen, Birgit Heese, Mika Komppula, Jana Preißler, Matthias Tesche, Albert Ansmann, Ulla Wandinger, Jae-Hyun Lim, Joon Young Ahn, Iwona S. Stachlewska, Vassilis Amiridis, Eleni Marinou, Patric Seifert, Julian Hofer, Annett Skupin, Florian Schneider, Stephanie Bohlmann, Andreas Foth, Sebastian Bley, Anne Pfüller, Eleni Giannakaki, Heikki Lihavainen, Yrjö Viisanen, Rakesh Kumar Hooda, Sérgio Nepomuceno Pereira, Daniele Bortoli, Frank Wagner, Ina Mattis, Lucja Janicka, Krzysztof M. Markowicz, Peggy Achtert, Paulo Artaxo, Theotonio Pauliquevis, Rodrigo A. F. Souza, Ved Prakesh Sharma, Pieter Gideon van Zyl, Johan Paul Beukes, Junying Sun, Erich G. Rohwer, Ruru Deng, Rodanthi-Elisavet Mamouri, and Felix Zamorano
Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016, https://doi.org/10.5194/acp-16-5111-2016, 2016
Short summary
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The findings from more than 10 years of global aerosol lidar measurements with Polly systems are summarized, and a data set of optical properties for specific aerosol types is given. An automated data retrieval algorithm for continuous Polly lidar observations is presented and discussed by means of a Saharan dust advection event in Leipzig, Germany. Finally, a statistic on the vertical aerosol distribution including the seasonal variability at PollyNET locations around the globe is presented.
Heike Kalesse, Wanda Szyrmer, Stefan Kneifel, Pavlos Kollias, and Edward Luke
Atmos. Chem. Phys., 16, 2997–3012, https://doi.org/10.5194/acp-16-2997-2016, https://doi.org/10.5194/acp-16-2997-2016, 2016
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Mixed-phase clouds are ubiquitous. Process-level understanding is needed to address the complexity of mixed-phase clouds and to improve their representation in models. This study illustrates steps to identify the impact of a microphysical process (riming) on cloud Doppler radar observations. It suggests that in situ observations of key ice properties are needed to complement radar observations before process-oriented studies can effectively evaluate ice microphysical parameterizations in models.
A. Foth, H. Baars, P. Di Girolamo, and B. Pospichal
Atmos. Chem. Phys., 15, 7753–7763, https://doi.org/10.5194/acp-15-7753-2015, https://doi.org/10.5194/acp-15-7753-2015, 2015
Short summary
Short summary
We present a method to derive water vapour profiles from Raman lidar measurements calibrated by the integrated water vapour from a collocated microwave radiometer. These simultaneous observations provide an operational and continuous measurement of water vapour profiles. The stability of the calibration factor allows for the calibration of the lidar even in the presence of clouds. Based on this approach, water vapour profiles can be retrieved during all non-precipitating conditions.
D. Duethmann, J. Zimmer, A. Gafurov, A. Güntner, D. Kriegel, B. Merz, and S. Vorogushyn
Hydrol. Earth Syst. Sci., 17, 2415–2434, https://doi.org/10.5194/hess-17-2415-2013, https://doi.org/10.5194/hess-17-2415-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Resolving the ambiguous direction of arrival of weak meteor radar trail echoes
Comparison of single-Doppler and multiple-Doppler wind retrievals in Hurricane Matthew (2016)
Insights into wind turbine reflectivity and radar cross-section (RCS) and their variability using X-band weather radar observations
Eddies in motion: visualizing boundary-layer turbulence above an open boreal peatland using UAS thermal videos
Assimilation of DAWN Doppler wind lidar data during the 2017 Convective Processes Experiment (CPEX): impact on precipitation and flow structure
Consistency of total column ozone measurements between the Brewer and Dobson spectroradiometers of the LKO Arosa and PMOD/WRC Davos
RainForest: a random forest algorithm for quantitative precipitation estimation over Switzerland
Ground-based temperature and humidity profiling: combining active and passive remote sensors
Statistically analyzing the effect of ionospheric irregularity on GNSS radio occultation atmospheric measurement
Detection of the melting level with polarimetric weather radar
Benoît Tournadre, Benoît Gschwind, Yves-Marie Saint-Drenan, Xuemei Chen, Rodrigo Amaro E Silva, and Philippe Blanc
Atmos. Meas. Tech., 15, 3683–3704, https://doi.org/10.5194/amt-15-3683-2022, https://doi.org/10.5194/amt-15-3683-2022, 2022
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Solar radiation received by the Earth's surface is valuable information for various fields like the photovoltaic industry or climate research. Pictures taken from satellites can be used to estimate the solar radiation from cloud reflectivity. Two issues for a good estimation are different instrumentations and orbits. We modify a widely used method that is today only used on geostationary satellites, so it can be applied on instruments on different orbits and with different sensitivities.
Alfonso Ferrone, Anne-Claire Billault-Roux, and Alexis Berne
Atmos. Meas. Tech., 15, 3569–3592, https://doi.org/10.5194/amt-15-3569-2022, https://doi.org/10.5194/amt-15-3569-2022, 2022
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The Micro Rain Radar PRO (MRR-PRO) is a meteorological radar, with a relevant set of features for deployment in remote locations. We developed an algorithm, named ERUO, for the processing of its measurements of snowfall. The algorithm addresses typical issues of the raw spectral data, such as interference lines, but also improves the quality and sensitivity of the radar variables. ERUO has been evaluated over four different datasets collected in Antarctica and in the Swiss Jura.
Isabell Krisch, Neil P. Hindley, Oliver Reitebuch, and Corwin J. Wright
Atmos. Meas. Tech., 15, 3465–3479, https://doi.org/10.5194/amt-15-3465-2022, https://doi.org/10.5194/amt-15-3465-2022, 2022
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The Aeolus satellite measures global height resolved profiles of wind along a certain line-of-sight. However, for atmospheric dynamics research, wind measurements along the three cardinal axes are most useful. This paper presents methods to convert the measurements into zonal and meridional wind components. By combining the measurements during ascending and descending orbits, we achieve good derivation of zonal wind (equatorward of 80° latitude) and meridional wind (poleward of 70° latitude).
Francisco J. Pérez-Invernón, Heidi Huntrieser, Thilo Erbertseder, Diego Loyola, Pieter Valks, Song Liu, Dale J. Allen, Kenneth E. Pickering, Eric J. Bucsela, Patrick Jöckel, Jos van Geffen, Henk Eskes, Sergio Soler, Francisco J. Gordillo-Vázquez, and Jeff Lapierre
Atmos. Meas. Tech., 15, 3329–3351, https://doi.org/10.5194/amt-15-3329-2022, https://doi.org/10.5194/amt-15-3329-2022, 2022
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Lightning, one of the major sources of nitrogen oxides in the atmosphere, contributes to the tropospheric concentration of ozone and to the oxidizing capacity of the atmosphere. In this work, we contribute to improving the estimation of lightning-produced nitrogen oxides in the Ebro Valley and the Pyrenees by using two different TROPOMI products and comparing the results.
Guy Delrieu, Anil Kumar Khanal, Frédéric Cazenave, and Brice Boudevillain
Atmos. Meas. Tech., 15, 3297–3314, https://doi.org/10.5194/amt-15-3297-2022, https://doi.org/10.5194/amt-15-3297-2022, 2022
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The RadAlp experiment aims at improving quantitative precipitation estimation in the Alps thanks to X-band polarimetric radars and in situ measurements deployed in Grenoble, France. We revisit the physics of propagation and attenuation of microwaves in rain. We perform a generalized sensitivity analysis in order to establish useful parameterization for attenuation corrections. Originality lies in the use of otherwise undesired mountain returns for constraining the considered physical model.
Julian Steinheuer, Carola Detring, Frank Beyrich, Ulrich Löhnert, Petra Friederichs, and Stephanie Fiedler
Atmos. Meas. Tech., 15, 3243–3260, https://doi.org/10.5194/amt-15-3243-2022, https://doi.org/10.5194/amt-15-3243-2022, 2022
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Doppler wind lidars (DWLs) allow the determination of wind profiles with high vertical resolution and thus provide an alternative to meteorological towers. We address the question of whether wind gusts can be derived since they are short-lived phenomena. Therefore, we compare different DWL configurations and develop a new method applicable to all of them. A fast continuous scanning mode that completes a full observation cycle within 3.4 s is found to be the best-performing configuration.
Sebastian Becker, André Ehrlich, Evelyn Jäkel, Tim Carlsen, Michael Schäfer, and Manfred Wendisch
Atmos. Meas. Tech., 15, 2939–2953, https://doi.org/10.5194/amt-15-2939-2022, https://doi.org/10.5194/amt-15-2939-2022, 2022
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Airborne radiation measurements are used to characterize the solar directional reflection of a mixture of Arctic sea ice and open-ocean surfaces in the transition zone between both surface types. The mixture reveals reflection properties of both surface types. It is shown that the directional reflection of the mixture can be reconstructed from the directional reflection of the individual surfaces, accounting for the special conditions present in the transition zone.
You Zhao, Chao Liu, Di Di, Ziqiang Ma, and Shihao Tang
Atmos. Meas. Tech., 15, 2791–2805, https://doi.org/10.5194/amt-15-2791-2022, https://doi.org/10.5194/amt-15-2791-2022, 2022
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A typhoon is a high-impact atmospheric phenomenon that causes most significant socioeconomic damage, and its precipitation observation is always needed for typhoon characteristics and disaster prevention. This study developed a typhoon precipitation fusion method to combine observations from satellite radiometers, rain gauges and reanalysis to provide much improved typhoon precipitation datasets.
Witali Krochin, Francisco Navas-Guzmán, David Kuhl, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 15, 2231–2249, https://doi.org/10.5194/amt-15-2231-2022, https://doi.org/10.5194/amt-15-2231-2022, 2022
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This study leverages atmospheric temperature measurements performed with a ground-based radiometer making use of data that was collected during a 4-year observational campaign applying a new retrieval algorithm that improves the maximal altitude range from 45 to 55 km. The measurements are validated against two independent data sets, MERRA2 reanalysis data and the meteorological analysis of NAVGEM-HA.
Lu Yao, Yi Liu, Dongxu Yang, Zhaonan Cai, Jing Wang, Chao Lin, Naimeng Lu, Daren Lyu, Longfei Tian, Maohua Wang, Zengshan Yin, Yuquan Zheng, and Sisi Wang
Atmos. Meas. Tech., 15, 2125–2137, https://doi.org/10.5194/amt-15-2125-2022, https://doi.org/10.5194/amt-15-2125-2022, 2022
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A physics-based SIF retrieval algorithm, IAPCAS/SIF, is introduced and applied to OCO-2 and TanSat measurements. The strong linear relationship between OCO-2 SIF retrieved by IAPCAS/SIF and the official product indicates the algorithm's reliability. The good consistency in the spatiotemporal patterns and magnitude of the OCO-2 and TanSat SIF products suggests that the combinative usage of multi-satellite products has potential and that such work would contribute to further research.
Biao Tong, Xiangfei Sun, Jiyang Fu, Yuncheng He, and Pakwai Chan
Atmos. Meas. Tech., 15, 1829–1848, https://doi.org/10.5194/amt-15-1829-2022, https://doi.org/10.5194/amt-15-1829-2022, 2022
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In recent years, there has been numerous research on tropical cyclone (TC) observation based on satellite cloud images (SCIs), but most methods are limited by low efficiency and subjectivity. To overcome subjectivity and improve efficiency of traditional methods, this paper uses deep learning technology to do further research on fingerprint identification of TCs. Results provide an automatic and objective method to distinguish TCs from SCIs and are convenient for subsequent research.
Marie Bouillon, Sarah Safieddine, Simon Whitburn, Lieven Clarisse, Filipe Aires, Victor Pellet, Olivier Lezeaux, Noëlle A. Scott, Marie Doutriaux-Boucher, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 1779–1793, https://doi.org/10.5194/amt-15-1779-2022, https://doi.org/10.5194/amt-15-1779-2022, 2022
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The IASI instruments have been observing Earth since 2007. We use a neural network to retrieve atmospheric temperatures. This new temperature data record is validated against other datasets and shows good agreement. We use this new dataset to compute trends over the 2008–2020 period. We found a warming of the troposphere, more important at the poles. In the stratosphere, we found that temperatures decrease everywhere except at the South Pole. The cooling is more pronounced at the South pole.
Maya Ben-Yami, Hilke Oetjen, Helen Brindley, William Cossich, Dulce Lajas, Tiziano Maestri, Davide Magurno, Piera Raspollini, Luca Sgheri, and Laura Warwick
Atmos. Meas. Tech., 15, 1755–1777, https://doi.org/10.5194/amt-15-1755-2022, https://doi.org/10.5194/amt-15-1755-2022, 2022
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Spectral emissivity is a key property of the Earth's surface. Few measurements exist in the far-infrared, despite recent work showing that its contribution is important for accurate modelling of global climate. In preparation for ESA’s EE9 FORUM mission (launch in 2026), this study takes the first steps towards the development of an operational emissivity retrieval for FORUM by investigating the sensitivity of the emissivity product to different physical and operational parameters.
Matthew A. Miller, Sandra E. Yuter, Nicole P. Hoban, Laura M. Tomkins, and Brian A. Colle
Atmos. Meas. Tech., 15, 1689–1702, https://doi.org/10.5194/amt-15-1689-2022, https://doi.org/10.5194/amt-15-1689-2022, 2022
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Apparent waves in the atmosphere and similar features in storm winds can be detected by taking the difference between successive Doppler weather radar scans measuring radar-relative storm air motions. Applying image filtering to the difference data better isolates the detected signal. This technique is a useful tool in weather research and forecasting since such waves can trigger or enhance precipitation.
Richard Müller and Uwe Pfeifroth
Atmos. Meas. Tech., 15, 1537–1561, https://doi.org/10.5194/amt-15-1537-2022, https://doi.org/10.5194/amt-15-1537-2022, 2022
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The great works of physics teach us that a central paradigm of science should be to make methods and theories as easy as possible and as complex as needed. This paper provides a brief review of remote sensing of solar surface irradiance based on this paradigm.
S. Joseph Munchak, Robert S. Schrom, Charles N. Helms, and Ali Tokay
Atmos. Meas. Tech., 15, 1439–1464, https://doi.org/10.5194/amt-15-1439-2022, https://doi.org/10.5194/amt-15-1439-2022, 2022
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The ability to measure snowfall with weather radar has greatly advanced with the development of techniques that utilize dual-polarization measurements, which provide information about the snow particle shape and orientation, and multi-frequency measurements, which provide information about size and density. This study combines these techniques with the NASA D3R radar, which provides dual-frequency polarimetric measurements, with data that were observed during the 2018 Winter Olympics.
Oliver Lux, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Benjamin Witschas, Stephan Rahm, Alexander Geiß, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 15, 1303–1331, https://doi.org/10.5194/amt-15-1303-2022, https://doi.org/10.5194/amt-15-1303-2022, 2022
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The article discusses modifications in the wind retrieval of the ALADIN Airborne Demonstrator (A2D) – one of the key instruments for the validation of Aeolus. Thanks to the retrieval refinements, which are demonstrated in the context of two airborne campaigns in 2019, the systematic and random wind errors of the A2D were significantly reduced, thereby enhancing its validation capabilities. Finally, wind comparisons between A2D and Aeolus for the validation of the satellite data are presented.
Terhikki Manninen, Emmihenna Jääskeläinen, Niilo Siljamo, Aku Riihelä, and Karl-Göran Karlsson
Atmos. Meas. Tech., 15, 879–893, https://doi.org/10.5194/amt-15-879-2022, https://doi.org/10.5194/amt-15-879-2022, 2022
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A new method for cloud-correcting observations of surface albedo is presented for AVHRR data. Instead of a binary cloud mask, it applies cloud probability values smaller than 20% of the A3 edition of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record provided by the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT. According to simulations, the 90% quantile was 1.1% for the absolute albedo error and 2.2% for the relative error.
Shihan Chen, Yuanjian Yang, Fei Deng, Yanhao Zhang, Duanyang Liu, Chao Liu, and Zhiqiu Gao
Atmos. Meas. Tech., 15, 735–756, https://doi.org/10.5194/amt-15-735-2022, https://doi.org/10.5194/amt-15-735-2022, 2022
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This paper proposes a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. The spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. The present RF model framework for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII.
Brian J. Carroll, Amin R. Nehrir, Susan A. Kooi, James E. Collins, Rory A. Barton-Grimley, Anthony Notari, David B. Harper, and Joseph Lee
Atmos. Meas. Tech., 15, 605–626, https://doi.org/10.5194/amt-15-605-2022, https://doi.org/10.5194/amt-15-605-2022, 2022
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HALO is a recently developed lidar system that demonstrates new technologies and advanced algorithms for profiling water vapor as well as aerosol and cloud properties. The high-resolution, high-accuracy measurements have unique advantages within the suite of atmospheric instrumentation, such as directly trading water vapor measurement resolution for precision. This paper provides the methodology and first water vapor results, showing agreement with in situ and spaceborne sounder measurements.
Irina V. Djalalova, David D. Turner, Laura Bianco, James M. Wilczak, James Duncan, Bianca Adler, and Daniel Gottas
Atmos. Meas. Tech., 15, 521–537, https://doi.org/10.5194/amt-15-521-2022, https://doi.org/10.5194/amt-15-521-2022, 2022
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In this paper we investigate the synergy obtained by combining active (radio acoustic sounding system – RASS) and passive (microwave radiometer) remote sensing observations to obtain temperature vertical profiles through a radiative transfer model. Inclusion of the RASS observations leads to more accurate temperature profiles from the surface to 5 km above ground, well above the maximum height of the RASS observations themselves (2000 m), when compared to the microwave radiometer used alone.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 15, 503–520, https://doi.org/10.5194/amt-15-503-2022, https://doi.org/10.5194/amt-15-503-2022, 2022
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In this work, we review the use of quasi-vertical profiles for monitoring the calibration of the radar differential reflectivity ZDR. We validate the proposed method by comparing its results against the traditional approach based on measurements taken at 90°; we observed good agreement as the errors are within 0.2 dB. Additionally, we compare the results of the proposed method with ZDR derived from disdrometers; the errors are reasonable considering factors discussed in the paper.
Katarzyna Ośródka and Jan Szturc
Atmos. Meas. Tech., 15, 261–277, https://doi.org/10.5194/amt-15-261-2022, https://doi.org/10.5194/amt-15-261-2022, 2022
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Weather radar data are used in weather monitoring and forecasting, but they are affected by numerous errors and require advanced corrections. Different systems are designed and implemented to suit specific local conditions, like the RADVOL-QC system. The radar errors are divided into several groups: disturbance by non-meteorological echoes (from the mountains, RLAN signals, wind turbines, etc.), beam blockage, attenuation, etc. Each of them has different properties and is corrected differently.
Hui Liu, Kevin Garrett, Kayo Ide, Ross Hoffman, and Katherine Lukens
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-20, https://doi.org/10.5194/amt-2022-20, 2022
Revised manuscript accepted for AMT
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A TLS regression is used to optimally estimate speed-dependent biases between Aeolus L2B winds and short-term (6-h) forecasts of NOAA’s FV3GFS. The winds for 1–7 September 2019 are analyzed. Clear speed-dependent biases for both Mie and Rayleigh winds are found, particularly in the lower troposphere and stratosphere of the tropics and Southern Hemisphere. The biases are underestimated by the OLS regression of Aeolus O-B on FV3GFS winds; but are overestimated on Aeolus winds.
Xingou Xu and Ad Stoffelen
Atmos. Meas. Tech., 14, 7435–7451, https://doi.org/10.5194/amt-14-7435-2021, https://doi.org/10.5194/amt-14-7435-2021, 2021
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The support vector machine can effectively represent the increasing effect of rain affecting wind speeds. This research provides a correction of deviations that are skew- to Gaussian-like features caused by rain in Ku-band scatterometer wind. It demonstrates the effectiveness of a machine learning method when used based on elaborate analysis of the model establishment and result validation procedures. The corrected winds provide information previously lacking, which is vital for nowcasting.
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.
Ryan Volz, Jorge L. Chau, Philip J. Erickson, Juha P. Vierinen, J. Miguel Urco, and Matthias Clahsen
Atmos. Meas. Tech., 14, 7199–7219, https://doi.org/10.5194/amt-14-7199-2021, https://doi.org/10.5194/amt-14-7199-2021, 2021
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We introduce a new way of estimating winds in the upper atmosphere (about 80 to 100 km in altitude) from the observed Doppler shift of meteor trails using a statistical method called Gaussian process regression. Wind estimates and, critically, the uncertainty of those estimates can be evaluated smoothly (i.e., not gridded) in space and time. The effective resolution is set by provided parameters, which are limited in practice by the number density of the observed meteors.
Fabian Weiler, Michael Rennie, Thomas Kanitz, Lars Isaksen, Elena Checa, Jos de Kloe, Ngozi Okunde, and Oliver Reitebuch
Atmos. Meas. Tech., 14, 7167–7185, https://doi.org/10.5194/amt-14-7167-2021, https://doi.org/10.5194/amt-14-7167-2021, 2021
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This paper summarizes the identification and correction of one of the most important systematic error sources for the wind measurements of the ESA satellite Aeolus. It depicts the effects of small temperature variations in the primary telescope mirror on the quality of the wind products and describes the approach to correct for it in the near-real-time processing. Moreover, the performance of the correction approach is assessed, and alternative approaches are discussed.
Xinyan Li, Yuanjian Yang, Jiaqin Mi, Xueyan Bi, You Zhao, Zehao Huang, Chao Liu, Lian Zong, and Wanju Li
Atmos. Meas. Tech., 14, 7007–7023, https://doi.org/10.5194/amt-14-7007-2021, https://doi.org/10.5194/amt-14-7007-2021, 2021
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A random forest (RF) model framework for Fengyun-4A (FY-4A) daytime and nighttime quantitative precipitation estimation (QPE) is established using FY-4A multi-band spectral information, cloud parameters, high-density precipitation observations and physical quantities from reanalysis data. The RF model of FY-4A QPE has a high accuracy in estimating precipitation at the heavy-rain level or below, which has advantages for quantitative estimation of summer precipitation over East Asia in future.
Clayton Cantrall and Tomoko Matsuo
Atmos. Meas. Tech., 14, 6917–6928, https://doi.org/10.5194/amt-14-6917-2021, https://doi.org/10.5194/amt-14-6917-2021, 2021
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This paper presents a new technique to determine temperature in the thermosphere from observations of far ultraviolet radiation emitted by molecular nitrogen. The technique utilizes a ratio of two far ultraviolet spectral channels to capture the thermosphere temperature signal. Applying the technique to NASA GOLD observations results in temperatures that agree well with other thermosphere observations during a geomagnetic disturbance.
Gunter Stober, Alexander Kozlovsky, Alan Liu, Zishun Qiao, Masaki Tsutsumi, Chris Hall, Satonori Nozawa, Mark Lester, Evgenia Belova, Johan Kero, Patrick J. Espy, Robert E. Hibbins, and Nicholas Mitchell
Atmos. Meas. Tech., 14, 6509–6532, https://doi.org/10.5194/amt-14-6509-2021, https://doi.org/10.5194/amt-14-6509-2021, 2021
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Wind observations at the edge to space, 70–110 km altitude, are challenging. Meteor radars have become a widely used instrument to obtain mean wind profiles above an instrument for these heights. We describe an advanced mathematical concept and present a tomographic analysis using several meteor radars located in Finland, Sweden and Norway, as well as Chile, to derive the three-dimensional flow field. We show an example of a gravity wave decelerating the mean flow.
Snizhana Ross, Arttu Arjas, Ilkka I. Virtanen, Mikko J. Sillanpää, Lassi Roininen, and Andreas Hauptmann
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-287, https://doi.org/10.5194/amt-2021-287, 2021
Revised manuscript accepted for AMT
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Radar measurements of thermal fluctuations in the Earth's ionosphere produce weak signals and tuning to specific altitudes results in suboptimal resolution for other regions, making an accurate analysis of these changes difficult. A novel approach to improve the resolution and remove measurement noise is considered. The method can capture variable characteristics, making it ideal for the study of a large range of data. Synthetically generated examples and two measured datasets were considered.
Corwin J. Wright, Neil P. Hindley, M. Joan Alexander, Laura A. Holt, and Lars Hoffmann
Atmos. Meas. Tech., 14, 5873–5886, https://doi.org/10.5194/amt-14-5873-2021, https://doi.org/10.5194/amt-14-5873-2021, 2021
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Measuring atmospheric gravity waves in low vertical-resolution data is technically challenging, especially when the waves are significantly longer in the vertical than in the length of the measurement domain. We introduce and demonstrate a modification to the existing Stockwell transform methods of characterising these waves that address these problems, with no apparent reduction in the other capabilities of the technique.
Tong Ning and Gunnar Elgered
Atmos. Meas. Tech., 14, 5593–5605, https://doi.org/10.5194/amt-14-5593-2021, https://doi.org/10.5194/amt-14-5593-2021, 2021
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We have estimated horizontal gradients of the propagation delay caused by water vapour in the atmosphere using two independent techniques, namely global navigation satellite systems (GNSS) and microwave radiometry. The highest resolution was 5 min. We found that the sampling of the atmosphere in different directions is an important factor for high correlations between the two techniques and that GNSS data can be used to detect large short-lived gradients, however, with increased formal errors.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
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Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
Benjamin Männel, Florian Zus, Galina Dick, Susanne Glaser, Maximilian Semmling, Kyriakos Balidakis, Jens Wickert, Marion Maturilli, Sandro Dahlke, and Harald Schuh
Atmos. Meas. Tech., 14, 5127–5138, https://doi.org/10.5194/amt-14-5127-2021, https://doi.org/10.5194/amt-14-5127-2021, 2021
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Within the MOSAiC expedition, GNSS was used to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked data, coordinates and hourly zenith total delays (ZTDs) were determined using kinematic precise point positioning. The derived ZTD values agree within few millimeters with ERA5 and terrestrial GNSS and VLBI stations. The derived integrated water vapor corresponds to the frequently launched radiosondes (0.08 ± 0.04 kg m−2, rms of the differences of 1.47 kg m−2).
Joel P. Younger, Iain M. Reid, Chris L. Adami, Chris M. Hall, and Masaki Tsutsumi
Atmos. Meas. Tech., 14, 5015–5027, https://doi.org/10.5194/amt-14-5015-2021, https://doi.org/10.5194/amt-14-5015-2021, 2021
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A radar in Svalbard usually used to study meteor trails was used to observe a thin icy layer in the upper atmosphere. New methods used the layer to measure wind speed over short periods of time and found that the layer is most reflective within 6.8 ± 3.3° of vertical. Analysis of meteor trail radar echo durations found that the layer may shorten meteor trail echoes, but more data are needed. This study shows new uses for data collected by meteor radars for other purposes.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
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Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, https://doi.org/10.5194/amt-14-4403-2021, 2021
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Planetary boundary layer (PBL) height is a critical parameter in atmospheric models. Continuous PBL height measurements from remote sensing measurements are important to understand various boundary layer mechanisms, especially during daytime and evening transition periods. Due to several limitations in existing methodologies to detect PBL height from a Doppler lidar, in this study, a machine learning (ML) approach is tested. The ML model is observed to improve the accuracy by over 50 %.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Anne Kleinert, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, Daniel R. Marsh, and Gabriele P. Stiller
Atmos. Meas. Tech., 14, 4111–4138, https://doi.org/10.5194/amt-14-4111-2021, https://doi.org/10.5194/amt-14-4111-2021, 2021
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An improved dataset of vertical temperature profiles of the Earth's atmosphere in the altitude range 5–70 km is presented. These profiles are derived from measurements of the MIPAS instrument onboard ESA's Envisat satellite. The overall improvements are based on upgrades in the input data and several improvements in the data processing approach. Both of these are discussed, and an extensive error discussion is included. Enhancements of the new dataset are demonstrated by means of examples.
Daniel Kastinen, Johan Kero, Alexander Kozlovsky, and Mark Lester
Atmos. Meas. Tech., 14, 3583–3596, https://doi.org/10.5194/amt-14-3583-2021, https://doi.org/10.5194/amt-14-3583-2021, 2021
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When a meteor enters the atmosphere, it causes a trail of diffusing plasma that moves with the neutral wind. An interferometric radar system can measure such trails and determine its location. However, there is a chance of determining the wrong position due to noise. We simulate this behaviour and use the simulations to successfully determine the true location of ambiguous events. We also successfully test two simple temporal integration methods for avoiding such erroneous determinations.
Ting-Yu Cha and Michael M. Bell
Atmos. Meas. Tech., 14, 3523–3539, https://doi.org/10.5194/amt-14-3523-2021, https://doi.org/10.5194/amt-14-3523-2021, 2021
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Doppler radar provides high-resolution wind measurements within tropical cyclones (TCs) for real-time monitoring and weather forecasting. Hurricane Matthew (2016) was observed by the ground-based single-Doppler and NOAA P-3 Hurricane Hunter airborne radar simultaneously, providing a novel opportunity to compare single- and multiple-Doppler wind retrieval techniques. Here, we improve the single-Doppler wind retrieval algorithm and show the pros and cons of each method for studying TC structure.
Martin Lainer, Jordi Figueras i Ventura, Zaira Schauwecker, Marco Gabella, Montserrat F.-Bolaños, Reto Pauli, and Jacopo Grazioli
Atmos. Meas. Tech., 14, 3541–3560, https://doi.org/10.5194/amt-14-3541-2021, https://doi.org/10.5194/amt-14-3541-2021, 2021
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We show results from two unique measurement campaigns aimed at better understanding effects of large wind turbines on radar returns by deploying a mobile X-band weather radar system in the proximity of a small wind park. Measurements were taken in 24/7 operation with dedicated scan strategies to retrieve the variability and most extreme values of reflectivity and radar cross-section of the wind turbines. The findings are useful for wind turbine interference mitigation measures in radar systems.
Pavel Alekseychik, Gabriel Katul, Ilkka Korpela, and Samuli Launiainen
Atmos. Meas. Tech., 14, 3501–3521, https://doi.org/10.5194/amt-14-3501-2021, https://doi.org/10.5194/amt-14-3501-2021, 2021
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Drones with thermal cameras are powerful new tools with the potential to provide new insights into atmospheric turbulence and heat fluxes. In a pioneering experiment, a Matrice 210 drone with a Zenmuse XT2 thermal camera was used to record 10–20 min thermal videos at 500 m a.g.l. over the Siikaneva peatland in southern Finland. A method to visualize the turbulent structures and derive their parameters from thermal videos is developed. The study provides a novel approach for turbulence analysis.
Svetla Hristova-Veleva, Sara Q. Zhang, F. Joseph Turk, Ziad S. Haddad, and Randy C. Sawaya
Atmos. Meas. Tech., 14, 3333–3350, https://doi.org/10.5194/amt-14-3333-2021, https://doi.org/10.5194/amt-14-3333-2021, 2021
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The assimilation of airborne-based three-dimensional winds into a mesoscale weather forecast model resulted in better agreement with airborne radar-derived precipitation 3-D structure at later model time steps. More importantly, there was also a discernible impact on the resultant wind and moisture structure, in accord with independent analysis of the wind structure and external satellite observations.
Julian Gröbner, Herbert Schill, Luca Egli, and René Stübi
Atmos. Meas. Tech., 14, 3319–3331, https://doi.org/10.5194/amt-14-3319-2021, https://doi.org/10.5194/amt-14-3319-2021, 2021
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The world's longest continuous total column ozone time series was initiated in 1926 at the Lichtklimatisches Observatorium (LKO), at Arosa, in the Swiss Alps. The measurements between Dobson and Brewer spectroradiometers have shown seasonal variations of the order of 2 %. The results of the study show that the consistency between the two instrument types can be significantly improved when the ozone cross-sections from Serdyuchenko et al. (2013) and the measured slit functions are used.
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 14, 3169–3193, https://doi.org/10.5194/amt-14-3169-2021, https://doi.org/10.5194/amt-14-3169-2021, 2021
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In this work, we present a novel quantitative precipitation estimation method for Switzerland that uses random forests, an ensemble-based machine learning technique. The estimator has been trained with a database of 4 years of ground and radar observations. The results of an in-depth evaluation indicate that, compared with the more classical method in use at MeteoSwiss, this novel estimator is able to reduce both the average error and bias of the predictions.
David D. Turner and Ulrich Löhnert
Atmos. Meas. Tech., 14, 3033–3048, https://doi.org/10.5194/amt-14-3033-2021, https://doi.org/10.5194/amt-14-3033-2021, 2021
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Temperature and humidity profiles in the lowest couple of kilometers near the surface are very important for many applications. Passive spectral radiometers are commercially available, and observations from these instruments have been used to get these profiles. However, new active lidar systems are able to measure partial profiles of water vapor. This paper investigates how the derived profiles of water vapor and temperature are improved when the active and passive observations are combined.
Mingzhe Li and Xinan Yue
Atmos. Meas. Tech., 14, 3003–3013, https://doi.org/10.5194/amt-14-3003-2021, https://doi.org/10.5194/amt-14-3003-2021, 2021
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In this study, we statistically analyzed the correlation between the ionospheric irregularity and the quality of the GNSS atmospheric radio occultation (RO) products. The results show that the ionospheric irregularity could affect the GNSS atmospheric RO in terms of causing failed inverted RO events and the bending angle oscillation. Awareness of the ionospheric irregularity effect on RO could be beneficial to improve the RO data quality for weather and climate research.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 14, 2873–2890, https://doi.org/10.5194/amt-14-2873-2021, https://doi.org/10.5194/amt-14-2873-2021, 2021
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In our paper, we propose a robust and operational algorithm to determine the height of the melting level that can be applied to either quasi-vertical profiles (QVPs) or vertical profiles (VPs) of polarimetric radar variables. The algorithm is applied to 1 year of rainfall events that occurred over southeast England and validated using radiosonde data. The algorithm proves to be accurate as the errors (mean absolute error and root mean square error) are close to 200 m.
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Short summary
In this paper, we present two micro rain radar-based approaches to discriminate between stratiform and convective precipitation. One is based on probability density functions and the other one is an artificial neural network classification. Both methods agree well, giving similar results. However, the results of the artificial neural network are more reasonable since it is also able to distinguish an inconclusive class, in turn making the stratiform and convective classes more reliable.
In this paper, we present two micro rain radar-based approaches to discriminate between...