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2. Determination of high-precision tropospheric delays using crowdsourced smartphone GNSS data.

Author

Pan, Yuanxin, Kłopotek, Grzegorz, Crocetti, Laura, Weinacker, Rudi, Sturn, Tobias, See, Linda, Dick, Galina, Möller, Gregor, Rothacher, Markus, McCallum, Ian, Navarro, Vicente, and Soja, Benedikt

Subjects
GLOBAL Positioning System, SATELLITE positioning, MULTISENSOR data fusion, MACHINE parts, MACHINE learning
Abstract

The Global Navigation Satellite System (GNSS) is a key asset for tropospheric monitoring. Currently, GNSS meteorology relies primarily on geodetic-grade stations. However, such stations are too costly to be densely deployed, which limits the contribution of GNSS to tropospheric monitoring. In 2016, Google released the raw GNSS measurement application programming interface for smartphones running on Android version 7.0 and higher. Given that nowadays there are billions of Android smartphones worldwide, utilizing those devices for atmospheric monitoring represents a remarkable scientific opportunity. In this study, smartphone GNSS data collected in Germany as part of the Application of Machine Learning Technology for GNSS IoT Data Fusion (CAMALIOT) crowdsourcing campaign in 2022 were utilized to investigate this idea. Approximately 20 000 raw GNSS observation files were collected there during the campaign. First, a dedicated data processing pipeline was established that consists of two major parts: machine learning (ML)-based data selection and ionosphere-free precise point positioning (PPP)-based zenith total delay (ZTD) estimation. The proposed method was validated with a dedicated smartphone data collection experiment conducted on the rooftop of the ETH campus. The results confirmed that ZTD estimates of millimeter-level precision could be achieved with smartphone data collected in an open-sky environment. The impacts of observation time span and utilization of multi-GNSS observations on ZTD estimation were also investigated. Subsequently, the crowdsourced data from Germany were processed by PPP with the ionospheric delays interpolated using observations from surrounding satellite positioning service of the German National Survey (SAPOS) GNSS stations. The ZTDs derived from ERA5 and an ML-based ZTD product served as benchmarks. The results revealed that an accuracy of better than 10 mm can be achieved by utilizing selected high-quality crowdsourced smartphone data. This study demonstrates high-precision ZTD determination with crowdsourced smartphone GNSS data and reveals success factors and current limitations. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Determination of High-Precision Tropospheric Delays Using Crowdsourced Smartphone GNSS Data.

Author

Yuanxin Pan, Kłopotek, Grzegorz, Crocetti, Laura, Weinacker, Rudi, Sturn, Tobias, See, Linda, Dick, Galina, Möller, Gregor, Rothacher, Markus, McCallum, Ian, Navarro, Vicente, and Soja, Benedikt

Subjects
GLOBAL Positioning System, MACHINE learning, SMARTPHONES
Abstract

The Global Navigation Satellite System (GNSS) is a key asset for tropospheric monitoring. Currently, GNSS meteorology relies primarily on geodetic-grade stations. However, such stations are too costly to be densely deployed, which limits the contribution of GNSS to tropospheric monitoring. In 2016, Google released the raw GNSS measurement application programming interface for smartphones running on Android version 7.0 and higher. Since nowadays there are billions of Android smartphones worldwide, utilizing those devices for atmospheric monitoring represents a remarkable scientific opportunity. In this study, smartphone GNSS data collected in Germany as part of the Application of Machine Learning Technology for GNSS IoT Data Fusion (CAMALIOT) crowdsourcing campaign in 2022 were utilized to investigate this idea. Approximately twenty thousand raw GNSS observation files were collected there during the campaign. First, a dedicated data processing pipeline was established that consists of two major parts: machine learning (ML)-based data selection and ionosphere-free Precise Point Positioning (PPP)-based Zenith Total Delay (ZTD) estimation. The proposed method was validated with a dedicated smartphone data collection experiment conducted on the rooftop of the ETH campus. The results confirmed that ZTD estimates of mm-level precision could be achieved with smartphone data collected in an open-sky environment. The impacts of observation time span and utilization of multi-GNSS observations on ZTD estimation were also investigated. Subsequently, the crowdsourced data from Germany were processed by PPP with the ionospheric delays interpolated using observations from surrounding SAPOS (Satellite Positioning Service of the German State Survey) GNSS stations. The ZTDs derived from ERA5 and an ML-based ZTD product served as benchmarks. The results revealed that an accuracy of better than 10 mm can be achieved by utilizing selected high-quality crowdsourced smartphone data. This study marks the first successful demonstration of high-precision ZTD determination with crowdsourced smartphone GNSS data and reveals success factors and current limitations. [ABSTRACT FROM AUTHOR]

Published
2024
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8. EUREC 4 A

Author

Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher, Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Albright, Anna Lea, Bellenger, Hugo, Bodenschatz, Eberhard, Caesar, Kathy-Ann, Chewitt-Lucas, Rebecca, de Boer, Gijs, Delanoë, Julien, Denby, Leif, Ewald, Florian, Fildier, Benjamin, Forde, Marvin, George, Geet, Gross, Silke, Hagen, Martin, Hausold, Andrea, Heywood, Karen J., Hirsch, Lutz, Jacob, Marek, Jansen, Friedhelm, Kinne, Stefan, Klocke, Daniel, Kölling, Tobias, Konow, Heike, Lothon, Marie, Mohr, Wiebke, Naumann, Ann Kristin, Nuijens, Louise, Olivier, Léa, Pincus, Robert, Pöhlker, Mira, Reverdin, Gilles, Roberts, Gregory, Schnitt, Sabrina, Schulz, Hauke, Siebesma, A. Pier, Stephan, Claudia Christine, Sullivan, Peter, Touzé-Peiffer, Ludovic, Vial, Jessica, Vogel, Raphaela, Zuidema, Paquita, Alexander, Nicola, Alves, Lyndon, Arixi, Sophian, Asmath, Hamish, Bagheri, Gholamhossein, Baier, Katharina, Bailey, Adriana, Baranowski, Dariusz, Baron, Alexandre, Barrau, Sébastien, Barrett, Paul A., Batier, Frédéric, Behrendt, Andreas, Bendinger, Arne, Beucher, Florent, Bigorre, Sebastien, Blades, Edmund, Blossey, Peter, Bock, Olivier, Böing, Steven, Bosser, Pierre, Bourras, Denis, Bouruet-Aubertot, Pascale, Bower, Keith, Branellec, Pierre, Branger, Hubert, Brennek, Michal, Brewer, Alan, Brilouet, Pierre-Etienne, Brügmann, Björn, Buehler, Stefan A., Burke, Elmo, Burton, Ralph, Calmer, Radiance, Canonici, Jean-Christophe, Carton, Xavier, Cato Jr., Gregory, Charles, Jude Andre, Chazette, Patrick, Chen, Yanxu, Chilinski, Michal T., Choularton, Thomas, Chuang, Patrick, Clarke, Shamal, Coe, Hugh, Cornet, Céline, Coutris, Pierre, Couvreux, Fleur, Crewell, Susanne, Cronin, Timothy, Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-Philippe, Dörner, Steffen, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dütsch, Marina, Ehrlich, André, Emanuel, Kerry, Emmanouilidis, Alexandros, Etienne, Jean-Claude, Etienne-Leblanc, Sheryl, Faure, Ghislain, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra, Gentemann, Chelle, Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, de Graaf, Dörte, de Groot, Geiske E., Grosz, Robert, Güttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Ibanez-Landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, Körner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Krüger, Ovid, Kumala, Wojciech, Kurz, Armin, L'Hégaret, Pierre, Labaste, Matthieu, Lachlan-Cope, Tom, Laing, Arlene, Landschützer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clément, Lavik, Gauke, Laxenaire, Rémi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolò, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-Als, Margarette, Mazel, Christophe, McGeary, Wayne, McWilliams, James C., Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter, Möller, Gregor, Morfa Avalos, Yanmichel, Muller, Caroline, Musat, Ionela, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, Philippi, Miriam, Plueddemann, Albert, Pöhlker, Christopher, Pörtge, Veronika, Pöschl, Ulrich, Pologne, Lawrence, Posyniak, Michał, Prange, Marc, Quiñones Meléndez, Estefanía, Radtke, Jule, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Röttenbacher, Johannes, Rollo, Callum, Royer, Haley, Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schäfer, Michael, Schemann, Vera, Schirmacher, Imke, Schlenczek, Oliver, Schmidt, Jerome, Schröder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Späth, Florian, Spooner, Branden, Stolla, M. Katharina, Szkółka, Wojciech, de Szoeke, Simon P., Tarot, Stéphane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Wulfmeyer, Volker, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Ziemen, Florian, Zinner, Tobias, Zöger, Martin, Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher, Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Albright, Anna Lea, Bellenger, Hugo, Bodenschatz, Eberhard, Caesar, Kathy-Ann, Chewitt-Lucas, Rebecca, de Boer, Gijs, Delanoë, Julien, Denby, Leif, Ewald, Florian, Fildier, Benjamin, Forde, Marvin, George, Geet, Gross, Silke, Hagen, Martin, Hausold, Andrea, Heywood, Karen J., Hirsch, Lutz, Jacob, Marek, Jansen, Friedhelm, Kinne, Stefan, Klocke, Daniel, Kölling, Tobias, Konow, Heike, Lothon, Marie, Mohr, Wiebke, Naumann, Ann Kristin, Nuijens, Louise, Olivier, Léa, Pincus, Robert, Pöhlker, Mira, Reverdin, Gilles, Roberts, Gregory, Schnitt, Sabrina, Schulz, Hauke, Siebesma, A. Pier, Stephan, Claudia Christine, Sullivan, Peter, Touzé-Peiffer, Ludovic, Vial, Jessica, Vogel, Raphaela, Zuidema, Paquita, Alexander, Nicola, Alves, Lyndon, Arixi, Sophian, Asmath, Hamish, Bagheri, Gholamhossein, Baier, Katharina, Bailey, Adriana, Baranowski, Dariusz, Baron, Alexandre, Barrau, Sébastien, Barrett, Paul A., Batier, Frédéric, Behrendt, Andreas, Bendinger, Arne, Beucher, Florent, Bigorre, Sebastien, Blades, Edmund, Blossey, Peter, Bock, Olivier, Böing, Steven, Bosser, Pierre, Bourras, Denis, Bouruet-Aubertot, Pascale, Bower, Keith, Branellec, Pierre, Branger, Hubert, Brennek, Michal, Brewer, Alan, Brilouet, Pierre-Etienne, Brügmann, Björn, Buehler, Stefan A., Burke, Elmo, Burton, Ralph, Calmer, Radiance, Canonici, Jean-Christophe, Carton, Xavier, Cato Jr., Gregory, Charles, Jude Andre, Chazette, Patrick, Chen, Yanxu, Chilinski, Michal T., Choularton, Thomas, Chuang, Patrick, Clarke, Shamal, Coe, Hugh, Cornet, Céline, Coutris, Pierre, Couvreux, Fleur, Crewell, Susanne, Cronin, Timothy, Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-Philippe, Dörner, Steffen, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dütsch, Marina, Ehrlich, André, Emanuel, Kerry, Emmanouilidis, Alexandros, Etienne, Jean-Claude, Etienne-Leblanc, Sheryl, Faure, Ghislain, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra, Gentemann, Chelle, Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, de Graaf, Dörte, de Groot, Geiske E., Grosz, Robert, Güttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Ibanez-Landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, Körner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Krüger, Ovid, Kumala, Wojciech, Kurz, Armin, L'Hégaret, Pierre, Labaste, Matthieu, Lachlan-Cope, Tom, Laing, Arlene, Landschützer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clément, Lavik, Gauke, Laxenaire, Rémi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolò, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-Als, Margarette, Mazel, Christophe, McGeary, Wayne, McWilliams, James C., Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter, Möller, Gregor, Morfa Avalos, Yanmichel, Muller, Caroline, Musat, Ionela, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, Philippi, Miriam, Plueddemann, Albert, Pöhlker, Christopher, Pörtge, Veronika, Pöschl, Ulrich, Pologne, Lawrence, Posyniak, Michał, Prange, Marc, Quiñones Meléndez, Estefanía, Radtke, Jule, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Röttenbacher, Johannes, Rollo, Callum, Royer, Haley, Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schäfer, Michael, Schemann, Vera, Schirmacher, Imke, Schlenczek, Oliver, Schmidt, Jerome, Schröder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Späth, Florian, Spooner, Branden, Stolla, M. Katharina, Szkółka, Wojciech, de Szoeke, Simon P., Tarot, Stéphane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Wulfmeyer, Volker, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Ziemen, Florian, Zinner, Tobias, and Zöger, Martin

Abstract

Abstract. The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.

Published
2023

9. Nanosatellites: The Next Big Chapter in Atmospheric Tomography

Author

Möller, Gregor and Kyrchei, Ivan

Subjects
GNSS, radio occultation, nanosatellites, singular value decomposition, wet refractivity
Abstract

Nanosatellite technology opens up new possibilities for earth observation. In the next decade, large satellite constellations will arise with hundreds, up to thousand of satellites in low earth orbit. A number of satellites will be equipped with rather low-cost sensors, such as GNSS receivers, suited for atmospheric monitoring. However, the future evolution in atmospheric science leans not only on densified observing systems but also on new, more complex analysis methods. In this regard, tomographic principles provide a unique opportunity for sensor fusion. The difficulty in performing the conversion of integral measurements into 3D images is that the signal ray path is not a straight line and the number of radio sources and detectors is limited with respect to the size of the object of interest. Therefore, the inverse problem is either solved linearly or iterative nonlinear. In this chapter, an overview about the individual solving techniques for the tomographic problem is presented, including strategies for removing deficiencies of the ill-posed problem by using truncated singular value decomposition and the L-curve technique. Applied to dense nanosatellite formations, a new quality in the reconstruction of the 3D water vapor distribution is obtained, which has the potential for leading to further advances in atmospheric science., Inverse Problems - Recent Advances and Applications, ISBN:978-1-80355-223-1, ISBN:978-1-80355-222-4, ISBN:978-1-80355-224-8

Published
2023
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12. Low-cost and smartphone GNSS sensors: current capabilities and perspectives for seismic and tropospheric monitoring applications

Author

Hohensinn, Roland, primary, Stauffer, Raphael, additional, Herrera Pinzón, Iván Darío, additional, Möller, Gregor, additional, Aichinger-Rosenberger, Matthias, additional, Rossi, Yara, additional, Pan, Yuanxin, additional, Kłopotek, Grzegorz, additional, Soja, Benedikt, additional, and Rothacher, Markus, additional

Published
2022
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15. Machine learning based multipath mitigation for high-precision GNSS data processing

Author

Pan, Yuanxin, Möller, Gregor, Hohensinn, Roland, and Soja, Benedikt

Abstract

Multipath is the main unmodeled error source hindering high-precision GNSS (Global Navigation Satellite System) data processing. Classical multipath mitigation methods, such as sidereal filtering (SF) and multipath hemispherical map (MHM), have certain disadvantages: they are either too complicated for implementation or not effective enough for multipath mitigation. In this study, we demonstrate that machine learning (ML) based models, such as random forest, can overcome these drawbacks by spatial interpolation over sky map and thus mitigate multipath effectively. 30 days of 1 Hz geodetic grade GPS data as well as 6 days of low-cost data are used to train and test the ML models. Based on a series of test cases, the best number of days for model training and the validity period for the models are discussed in this contribution. For quantification, the multipath reduction rate and kinematic positioning precision are computed using different ML models and compared to those derived from SF and MHM. The statistical results show that the XGBoost ML model can achieve higher multipath reduction rates compared to SF and MHM, especially for pseudorange measurements, which is important for low-cost devices. It reduces the multipath by 48% and 55% for pseudorange and carrier phase measurements, respectively, and outperforms SF (40% and 52%) and MHM (37% and 49%). The positioning precision when using different multipath models is similar, with differences of less than 1 mm. We conclude that the ML based multipath mitigation method is effective and easy-to-use, which can be applied under real-time scenarios., EGUsphere

Published
2022
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17. EUREC<sup>4</sup>A

Author

Stevens, Bjorn, primary, Bony, Sandrine, additional, Farrell, David, additional, Ament, Felix, additional, Blyth, Alan, additional, Fairall, Christopher, additional, Karstensen, Johannes, additional, Quinn, Patricia K., additional, Speich, Sabrina, additional, Acquistapace, Claudia, additional, Aemisegger, Franziska, additional, Albright, Anna Lea, additional, Bellenger, Hugo, additional, Bodenschatz, Eberhard, additional, Caesar, Kathy-Ann, additional, Chewitt-Lucas, Rebecca, additional, de Boer, Gijs, additional, Delanoë, Julien, additional, Denby, Leif, additional, Ewald, Florian, additional, Fildier, Benjamin, additional, Forde, Marvin, additional, George, Geet, additional, Gross, Silke, additional, Hagen, Martin, additional, Hausold, Andrea, additional, Heywood, Karen J., additional, Hirsch, Lutz, additional, Jacob, Marek, additional, Jansen, Friedhelm, additional, Kinne, Stefan, additional, Klocke, Daniel, additional, Kölling, Tobias, additional, Konow, Heike, additional, Lothon, Marie, additional, Mohr, Wiebke, additional, Naumann, Ann Kristin, additional, Nuijens, Louise, additional, Olivier, Léa, additional, Pincus, Robert, additional, Pöhlker, Mira, additional, Reverdin, Gilles, additional, Roberts, Gregory, additional, Schnitt, Sabrina, additional, Schulz, Hauke, additional, Siebesma, A. Pier, additional, Stephan, Claudia Christine, additional, Sullivan, Peter, additional, Touzé-Peiffer, Ludovic, additional, Vial, Jessica, additional, Vogel, Raphaela, additional, Zuidema, Paquita, additional, Alexander, Nicola, additional, Alves, Lyndon, additional, Arixi, Sophian, additional, Asmath, Hamish, additional, Bagheri, Gholamhossein, additional, Baier, Katharina, additional, Bailey, Adriana, additional, Baranowski, Dariusz, additional, Baron, Alexandre, additional, Barrau, Sébastien, additional, Barrett, Paul A., additional, Batier, Frédéric, additional, Behrendt, Andreas, additional, Bendinger, Arne, additional, Beucher, Florent, additional, Bigorre, Sebastien, additional, Blades, Edmund, additional, Blossey, Peter, additional, Bock, Olivier, additional, Böing, Steven, additional, Bosser, Pierre, additional, Bourras, Denis, additional, Bouruet-Aubertot, Pascale, additional, Bower, Keith, additional, Branellec, Pierre, additional, Branger, Hubert, additional, Brennek, Michal, additional, Brewer, Alan, additional, Brilouet, Pierre-Etienne, additional, Brügmann, Björn, additional, Buehler, Stefan A., additional, Burke, Elmo, additional, Burton, Ralph, additional, Calmer, Radiance, additional, Canonici, Jean-Christophe, additional, Carton, Xavier, additional, Cato Jr., Gregory, additional, Charles, Jude Andre, additional, Chazette, Patrick, additional, Chen, Yanxu, additional, Chilinski, Michal T., additional, Choularton, Thomas, additional, Chuang, Patrick, additional, Clarke, Shamal, additional, Coe, Hugh, additional, Cornet, Céline, additional, Coutris, Pierre, additional, Couvreux, Fleur, additional, Crewell, Susanne, additional, Cronin, Timothy, additional, Cui, Zhiqiang, additional, Cuypers, Yannis, additional, Daley, Alton, additional, Damerell, Gillian M., additional, Dauhut, Thibaut, additional, Deneke, Hartwig, additional, Desbios, Jean-Philippe, additional, Dörner, Steffen, additional, Donner, Sebastian, additional, Douet, Vincent, additional, Drushka, Kyla, additional, Dütsch, Marina, additional, Ehrlich, André, additional, Emanuel, Kerry, additional, Emmanouilidis, Alexandros, additional, Etienne, Jean-Claude, additional, Etienne-Leblanc, Sheryl, additional, Faure, Ghislain, additional, Feingold, Graham, additional, Ferrero, Luca, additional, Fix, Andreas, additional, Flamant, Cyrille, additional, Flatau, Piotr Jacek, additional, Foltz, Gregory R., additional, Forster, Linda, additional, Furtuna, Iulian, additional, Gadian, Alan, additional, Galewsky, Joseph, additional, Gallagher, Martin, additional, Gallimore, Peter, additional, Gaston, Cassandra, additional, Gentemann, Chelle, additional, Geyskens, Nicolas, additional, Giez, Andreas, additional, Gollop, John, additional, Gouirand, Isabelle, additional, Gourbeyre, Christophe, additional, de Graaf, Dörte, additional, de Groot, Geiske E., additional, Grosz, Robert, additional, Güttler, Johannes, additional, Gutleben, Manuel, additional, Hall, Kashawn, additional, Harris, George, additional, Helfer, Kevin C., additional, Henze, Dean, additional, Herbert, Calvert, additional, Holanda, Bruna, additional, Ibanez-Landeta, Antonio, additional, Intrieri, Janet, additional, Iyer, Suneil, additional, Julien, Fabrice, additional, Kalesse, Heike, additional, Kazil, Jan, additional, Kellman, Alexander, additional, Kidane, Abiel T., additional, Kirchner, Ulrike, additional, Klingebiel, Marcus, additional, Körner, Mareike, additional, Kremper, Leslie Ann, additional, Kretzschmar, Jan, additional, Krüger, Ovid, additional, Kumala, Wojciech, additional, Kurz, Armin, additional, L'Hégaret, Pierre, additional, Labaste, Matthieu, additional, Lachlan-Cope, Tom, additional, Laing, Arlene, additional, Landschützer, Peter, additional, Lang, Theresa, additional, Lange, Diego, additional, Lange, Ingo, additional, Laplace, Clément, additional, Lavik, Gauke, additional, Laxenaire, Rémi, additional, Le Bihan, Caroline, additional, Leandro, Mason, additional, Lefevre, Nathalie, additional, Lena, Marius, additional, Lenschow, Donald, additional, Li, Qiang, additional, Lloyd, Gary, additional, Los, Sebastian, additional, Losi, Niccolò, additional, Lovell, Oscar, additional, Luneau, Christopher, additional, Makuch, Przemyslaw, additional, Malinowski, Szymon, additional, Manta, Gaston, additional, Marinou, Eleni, additional, Marsden, Nicholas, additional, Masson, Sebastien, additional, Maury, Nicolas, additional, Mayer, Bernhard, additional, Mayers-Als, Margarette, additional, Mazel, Christophe, additional, McGeary, Wayne, additional, McWilliams, James C., additional, Mech, Mario, additional, Mehlmann, Melina, additional, Meroni, Agostino Niyonkuru, additional, Mieslinger, Theresa, additional, Minikin, Andreas, additional, Minnett, Peter, additional, Möller, Gregor, additional, Morfa Avalos, Yanmichel, additional, Muller, Caroline, additional, Musat, Ionela, additional, Napoli, Anna, additional, Neuberger, Almuth, additional, Noisel, Christophe, additional, Noone, David, additional, Nordsiek, Freja, additional, Nowak, Jakub L., additional, Oswald, Lothar, additional, Parker, Douglas J., additional, Peck, Carolyn, additional, Person, Renaud, additional, Philippi, Miriam, additional, Plueddemann, Albert, additional, Pöhlker, Christopher, additional, Pörtge, Veronika, additional, Pöschl, Ulrich, additional, Pologne, Lawrence, additional, Posyniak, Michał, additional, Prange, Marc, additional, Quiñones Meléndez, Estefanía, additional, Radtke, Jule, additional, Ramage, Karim, additional, Reimann, Jens, additional, Renault, Lionel, additional, Reus, Klaus, additional, Reyes, Ashford, additional, Ribbe, Joachim, additional, Ringel, Maximilian, additional, Ritschel, Markus, additional, Rocha, Cesar B., additional, Rochetin, Nicolas, additional, Röttenbacher, Johannes, additional, Rollo, Callum, additional, Royer, Haley, additional, Sadoulet, Pauline, additional, Saffin, Leo, additional, Sandiford, Sanola, additional, Sandu, Irina, additional, Schäfer, Michael, additional, Schemann, Vera, additional, Schirmacher, Imke, additional, Schlenczek, Oliver, additional, Schmidt, Jerome, additional, Schröder, Marcel, additional, Schwarzenboeck, Alfons, additional, Sealy, Andrea, additional, Senff, Christoph J., additional, Serikov, Ilya, additional, Shohan, Samkeyat, additional, Siddle, Elizabeth, additional, Smirnov, Alexander, additional, Späth, Florian, additional, Spooner, Branden, additional, Stolla, M. Katharina, additional, Szkółka, Wojciech, additional, de Szoeke, Simon P., additional, Tarot, Stéphane, additional, Tetoni, Eleni, additional, Thompson, Elizabeth, additional, Thomson, Jim, additional, Tomassini, Lorenzo, additional, Totems, Julien, additional, Ubele, Alma Anna, additional, Villiger, Leonie, additional, von Arx, Jan, additional, Wagner, Thomas, additional, Walther, Andi, additional, Webber, Ben, additional, Wendisch, Manfred, additional, Whitehall, Shanice, additional, Wiltshire, Anton, additional, Wing, Allison A., additional, Wirth, Martin, additional, Wiskandt, Jonathan, additional, Wolf, Kevin, additional, Worbes, Ludwig, additional, Wright, Ethan, additional, Wulfmeyer, Volker, additional, Young, Shanea, additional, Zhang, Chidong, additional, Zhang, Dongxiao, additional, Ziemen, Florian, additional, Zinner, Tobias, additional, and Zöger, Martin, additional

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2021
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18. Deployment of the C-band radar Poldirad on Barbados during EUREC4A

Author

Hagen, Martin, primary, Ewald, Florian, additional, Groß, Silke, additional, Oswald, Lothar, additional, Farrell, David A., additional, Forde, Marvin, additional, Gutleben, Manuel, additional, Heumos, Johann, additional, Reimann, Jens, additional, Tetoni, Eleni, additional, Marinou, Eleni, additional, Möller, Gregor, additional, Kiemle, Christoph, additional, Li, Qiang, additional, Chewitt-Lucas, Rebecca, additional, Daley, Alton, additional, Grant, Delando, additional, and Hall, Kashawn, additional

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2021
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20. Overview: Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes

Author

Trömel, Silke, primary, Simmer, Clemens, additional, Blahak, Ulrich, additional, Blanke, Armin, additional, Ewald, Florian, additional, Frech, Michael, additional, Gergely, Mathias, additional, Hagen, Martin, additional, Hörnig, Sabine, additional, Janjic, Tijana, additional, Kalesse, Heike, additional, Kneifel, Stefan, additional, Knote, Christoph, additional, Mendrok, Jana, additional, Moser, Manuel, additional, Möller, Gregor, additional, Mühlbauer, Kai, additional, Myagkov, Alexander, additional, Pejcic, Velibor, additional, Seifert, Patric, additional, Shrestha, Prabhakar, additional, Teisseire, Audrey, additional, von Terzi, Leoni, additional, Tetoni, Eleni, additional, Vogl, Teresa, additional, Voigt, Christiane, additional, Zeng, Yuefei, additional, Zinner, Tobias, additional, and Quaas, Johannes, additional

Published
2021
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22. EUREC4A

Author

Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher W., Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Albright, Anna Lea, Bellenger, Hugo, Bodenschatz, Eberhard, Caesar, Kathy-Ann, Chewitt-Lucas, Rebecca, de Boer, Gijs, Delanoë, Julien, Denby, Leif, Ewald, Florian, Fildier, Benjamin, Forde, Marvin, George, Geet, Gross, Silke, Hagen, Martin, Hausold, Andrea, Heywood, Karen J., Hirsch, Lutz, Jacob, Marek, Jansen, Friedhelm, Kinne, Stefan, Klocke, Daniel, Kölling, Tobias, Konow, Heike, Lothon, Marie, Mohr, Wiebke, Naumann, Ann Kristin, Nuijens, Louise, Olivier, Léa, Pincus, Robert, Pöhlker, Mira L., Reverdin, Gilles, Roberts, Gregory, Schnitt, Sabrina, Schulz, Hauke, Siebesma, Pier, Stephan, Claudia Christine, Sullivan, Peter P., Touzé-Peiffer, Ludovic, Vial, Jessica, Vogel, Raphaela, Zuidema, Paquita, Alexander, Nicola, Alves, Lyndon, Arixi, Sophian, Asmath, Hamish, Bagheri, Gholamhossein, Baier, Katharina, Bailey, Adriana, Baranowski, Dariusz, Baron, Alexandre, Barrau, Sébastien, Barrett, Paul A., Batier, Frédéric, Behrendt, Andreas, Bendinger, Arne, Beucher, Florent, Bigorre, Sebastien P., Blades, Edmund, Blossey, Peter, Bock, Olivier, Böing, Steven, Bosser, Pierre, Bourras, Denis, Bouruet-Aubertot, Pascale, Bower, Keith, Branellec, Pierre, Branger, Hubert, Brennek, Michal, Brewer, Alan, Brilouet, Pierre-Etienne, Brügmann, Björn, Buehler, Stefan A., Burke, Elmo, Burton, Ralph, Calmer, Radiance, Canonici, Jean-Christophe, Carton, Xavier, Cato, Gregory, Jr., Charles, Jude Andre, Chazette, Patrick, Chen, Yanxu, Chilinski, Michal T., Choularton, Thomas, Chuang, Patrick, Clarke, Shamal, Coe, Hugh, Cornet, Céline, Coutris, Pierre, Couvreux, Fleur, Crewell, Susanne, Cronin, Timothy W., Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-Philippe, Dörner, Steffen, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dütsch, Marina, Ehrlich, André, Emanuel, Kerry A., Emmanouilidis, Alexandros, Etienne, Jean-Claude, Etienne-Leblanc, Sheryl, Faure, Ghislain, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra J., Gentemann, Chelle L., Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, de Graaf, Dörte, de Graaf, Geiske E., Grosz, Robert, Güttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Ibanez-Landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, Körner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Krüger, Ovid O., Kumala, Wojciech, Kurz, Armin, L'Hégareta, Pierre, Labaste, Matthieu, Lachlan-Cope, Thomas, Laing, Arlene, Landschützer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clément, Lavik, Gauke, Laxenaire, Rémi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolò, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-Als, Margarette, Mazel, Christophe, McGeary, Wayne, McWilliams, James C., Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter J., Möller, Gregor, Morfa Avalos, Yanmichel, Muller, Caroline, Musat, Ionela, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, Philippi, Miriam, Plueddemann, Albert J., Pöhlker, Christopher, Pörtge, Veronika, Pöschl, Ulrich, Pologne, Lawrence, Posyniak, Michał, Prange, Marc, Quinones Melendez, Estefania, Radtke, Jule, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Röttenbacher, Johannes, Rollo, Callum, Royer, Haley M., Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schäfer, Michael, Schemann, Vera, Schirmacher, Imke, Schlenczek, Oliver, Schmidt, Jerome M., Schröder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Späth, Florian, Spooner, Branden, Stolla, M. Katharina, Szkółka, Wojciech, de Szoeke, Simon P., Tarot, Stéphane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Ziemen, Florian, Zinner, Tobias, Zöger, Martin, Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher W., Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Albright, Anna Lea, Bellenger, Hugo, Bodenschatz, Eberhard, Caesar, Kathy-Ann, Chewitt-Lucas, Rebecca, de Boer, Gijs, Delanoë, Julien, Denby, Leif, Ewald, Florian, Fildier, Benjamin, Forde, Marvin, George, Geet, Gross, Silke, Hagen, Martin, Hausold, Andrea, Heywood, Karen J., Hirsch, Lutz, Jacob, Marek, Jansen, Friedhelm, Kinne, Stefan, Klocke, Daniel, Kölling, Tobias, Konow, Heike, Lothon, Marie, Mohr, Wiebke, Naumann, Ann Kristin, Nuijens, Louise, Olivier, Léa, Pincus, Robert, Pöhlker, Mira L., Reverdin, Gilles, Roberts, Gregory, Schnitt, Sabrina, Schulz, Hauke, Siebesma, Pier, Stephan, Claudia Christine, Sullivan, Peter P., Touzé-Peiffer, Ludovic, Vial, Jessica, Vogel, Raphaela, Zuidema, Paquita, Alexander, Nicola, Alves, Lyndon, Arixi, Sophian, Asmath, Hamish, Bagheri, Gholamhossein, Baier, Katharina, Bailey, Adriana, Baranowski, Dariusz, Baron, Alexandre, Barrau, Sébastien, Barrett, Paul A., Batier, Frédéric, Behrendt, Andreas, Bendinger, Arne, Beucher, Florent, Bigorre, Sebastien P., Blades, Edmund, Blossey, Peter, Bock, Olivier, Böing, Steven, Bosser, Pierre, Bourras, Denis, Bouruet-Aubertot, Pascale, Bower, Keith, Branellec, Pierre, Branger, Hubert, Brennek, Michal, Brewer, Alan, Brilouet, Pierre-Etienne, Brügmann, Björn, Buehler, Stefan A., Burke, Elmo, Burton, Ralph, Calmer, Radiance, Canonici, Jean-Christophe, Carton, Xavier, Cato, Gregory, Jr., Charles, Jude Andre, Chazette, Patrick, Chen, Yanxu, Chilinski, Michal T., Choularton, Thomas, Chuang, Patrick, Clarke, Shamal, Coe, Hugh, Cornet, Céline, Coutris, Pierre, Couvreux, Fleur, Crewell, Susanne, Cronin, Timothy W., Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-Philippe, Dörner, Steffen, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dütsch, Marina, Ehrlich, André, Emanuel, Kerry A., Emmanouilidis, Alexandros, Etienne, Jean-Claude, Etienne-Leblanc, Sheryl, Faure, Ghislain, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra J., Gentemann, Chelle L., Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, de Graaf, Dörte, de Graaf, Geiske E., Grosz, Robert, Güttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Ibanez-Landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, Körner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Krüger, Ovid O., Kumala, Wojciech, Kurz, Armin, L'Hégareta, Pierre, Labaste, Matthieu, Lachlan-Cope, Thomas, Laing, Arlene, Landschützer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clément, Lavik, Gauke, Laxenaire, Rémi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolò, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-Als, Margarette, Mazel, Christophe, McGeary, Wayne, McWilliams, James C., Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter J., Möller, Gregor, Morfa Avalos, Yanmichel, Muller, Caroline, Musat, Ionela, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, Philippi, Miriam, Plueddemann, Albert J., Pöhlker, Christopher, Pörtge, Veronika, Pöschl, Ulrich, Pologne, Lawrence, Posyniak, Michał, Prange, Marc, Quinones Melendez, Estefania, Radtke, Jule, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Röttenbacher, Johannes, Rollo, Callum, Royer, Haley M., Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schäfer, Michael, Schemann, Vera, Schirmacher, Imke, Schlenczek, Oliver, Schmidt, Jerome M., Schröder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Späth, Florian, Spooner, Branden, Stolla, M. Katharina, Szkółka, Wojciech, de Szoeke, Simon P., Tarot, Stéphane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Ziemen, Florian, Zinner, Tobias, and Zöger, Martin

Abstract

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Stevens, B., Bony, S., Farrell, D., Ament, F., Blyth, A., Fairall, C., Karstensen, J., Quinn, P. K., Speich, S., Acquistapace, C., Aemisegger, F., Albright, A. L., Bellenger, H., Bodenschatz, E., Caesar, K.-A., Chewitt-Lucas, R., de Boer, G., Delanoë, J., Denby, L., Ewald, F., Fildier, B., Forde, M., George, G., Gross, S., Hagen, M., Hausold, A., Heywood, K. J., Hirsch, L., Jacob, M., Jansen, F., Kinne, S., Klocke, D., Kölling, T., Konow, H., Lothon, M., Mohr, W., Naumann, A. K., Nuijens, L., Olivier, L., Pincus, R., Pöhlker, M., Reverdin, G., Roberts, G., Schnitt, S., Schulz, H., Siebesma, A. P., Stephan, C. C., Sullivan, P., Touzé-Peiffer, L., Vial, J., Vogel, R., Zuidema, P., Alexander, N., Alves, L., Arixi, S., Asmath, H., Bagheri, G., Baier, K., Bailey, A., Baranowski, D., Baron, A., Barrau, S., Barrett, P. A., Batier, F., Behrendt, A., Bendinger, A., Beucher, F., Bigorre, S., Blades, E., Blossey, P., Bock, O., Böing, S., Bosser, P., Bourras, D., Bouruet-Aubertot, P., Bower, K., Branellec, P., Branger, H., Brennek, M., Brewer, A., Brilouet , P.-E., Brügmann, B., Buehler, S. A., Burke, E., Burton, R., Calmer, R., Canonici, J.-C., Carton, X., Cato Jr., G., Charles, J. A., Chazette, P., Chen, Y., Chilinski, M. T., Choularton, T., Chuang, P., Clarke, S., Coe, H., Cornet, C., Coutris, P., Couvreux, F., Crewell, S., Cronin, T., Cui, Z., Cuypers, Y., Daley, A., Damerell, G. M., Dauhut, T., Deneke, H., Desbios, J.-P., Dörner, S., Donner, S., Douet, V., Drushka, K., Dütsch, M., Ehrlich, A., Emanuel, K., Emmanouilidis, A., Etienne, J.-C., Etienne-Leblanc, S., Faure, G., Feingold, G., Ferrero, L., Fix, A., Flamant, C., Flatau, P. J., Foltz, G. R., Forster, L., Furtuna, I., Gadian, A., Galewsky, J., Gallagher, M., Gallimore, P., Gaston, C., Gentemann, C., Geyskens, N., Giez, A., Gollop, J., Gouirand, I., Gourbeyre, C., de G, The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement., This research has been supported by the people and government of Barbados; the Max Planck Society and its supporting members; the German Research Foundation (DFG) and the German Federal Ministry of Education and Research (grant nos. GPF18-1_69 and GPF18-2_50); the European Research Council (ERC) advanced grant EUREC4A (grant agreement no. 694768) under the European Union’s Horizon 2020 research and innovation program (H2020), with additional support from CNES (the French National Centre for Space Studies) through the EECLAT proposal, Météo-France, the CONSTRAIN H2020 project (grant agreement no. 820829), and the French AERIS Research Infrastructure; the Natural Environment Research Council (NE/S015868/1, NE/S015752/1, and NE/S015779/1); ERC under the European Union’s H2020 program (COMPASS, advanced grant agreement no. 74110); the French national program LEFE INSU, by IFREMER, the French research fleet, CNES, the French research infrastructures AERIS and ODATIS, IPSL, the Chaire Chanel program of the Geosciences Department at ENS, and the European Union's Horizon 2020 research and innovation program under grant agreement no. 817578 TRIATLAS; NOAA’s Climate Variability and Prediction Program within the Climate Program Office (grant nos. GC19-305 and GC19-301); NOAA cooperative agreement NA15OAR4320063; NOAA's Climate Program Office and base funds to NOAA/AOML's Physical Oceanography Division; Swiss National Science Foundation grant no. 188731; the UAS Program Office, Climate Program Office, and Physical Sciences Laboratory and by the US National Science Foundation (NSF) through grant AGS-1938108; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2037 “CLICCS – Climate, Climatic Change, and Society” – project no. 390683824; and Poland’s National Science Centre grant no. UMO-2018/30/M/ST10/00674 and Foundation for Polish Science grant no. POIR.04.04.00-00-3FD6/17-02.

Published
2021

26. EUREC4A

Author

Stevens, Bjorn, primary, Bony, Sandrine, additional, Farrell, David, additional, Ament, Felix, additional, Blyth, Alan M., additional, Fairall, Christopher W., additional, Karstensen, Johannes, additional, Quinn, Patricia K., additional, Speich, Sabrina, additional, Acquistapace, Claudia, additional, Aemisegger, Franziska, additional, Albright, Anna Lea, additional, Bellenger, Hugo, additional, Bodenschatz, Eberhard, additional, Caesar, Kathy-Ann, additional, Chewitt-Lucas, Rebecca, additional, de Boer, Gijs, additional, Delanoë, Julien, additional, Denby, Leif Christopher, additional, Ewald, Florian, additional, Fildier, Benjamin, additional, Forde, Marvin, additional, George, Geet, additional, Gross, Silke, additional, Hagen, Martin, additional, Hausold, Andrea, additional, Heywood, Karen J., additional, Hirsch, Lutz, additional, Jacob, Marek, additional, Jansen, Friedhelm, additional, Kinne, Stefan, additional, Klocke, Daniel, additional, Kölling, Tobias, additional, Konow, Heike, additional, Lothon, Marie, additional, Mohr, Wiebke, additional, Naumann, Ann Kristin, additional, Nuijens, Louise, additional, Olivier, Léa, additional, Pincus, Robert, additional, Pöhlker, Mira L., additional, Reverdin, Gilles, additional, Roberts, Gregory, additional, Schnitt, Sabrina, additional, Schulz, Hauke, additional, Siebesma, Pier, additional, Stephan, Claudia Christine, additional, Sullivan, Peter P, additional, Touzé-Peiffer, Ludovic, additional, Vial, Jessica, additional, Vogel, Raphaela, additional, Zuidema, Paquita, additional, Alexander, Nicola, additional, Alves, Lyndon, additional, Arixi, Sophian, additional, Asmath, Hamish, additional, Bagheri, Gholamhossein, additional, Baier, Katharina, additional, Bailey, Adriana, additional, Baranowski, Dariusz B., additional, Baron, Alexandre, additional, Barrau, Sébastien, additional, Barrett, Paul Alan, additional, Batier, Frédéric, additional, Behrendt, Andreas, additional, Bendinger, Arne, additional, Beucher, Florent, additional, Bigorre, Sebastien, additional, Blades, Edmund, additional, Bock, Olivier, additional, Boeing, Steven J, additional, Bosser, Pierre, additional, Bourras, Denis, additional, Bouruet-Aubertot, Pascale, additional, Bower, Keith, additional, Branellec, Pierre, additional, Branger, Hubert, additional, Brennek, Michal, additional, Brewer, Alan, additional, Brilouet, Pierre-Etienne, additional, Brügmann, Björn, additional, Buehler, Stefan Alexander, additional, Burke, Elmo, additional, Burton, Ralph, additional, Calmer, Radiance, additional, Canonici, Jean-Christophe, additional, Carton, Xavier J., additional, Cato, Gregory, additional, Charles, Jude Andre, additional, Chazette, Patrick, additional, Chen, Yanxu, additional, Chiliński, Michał T, additional, Choularton, Tom, additional, Chuang, Patrick Y., additional, Clarke, Shamal, additional, Coe, Hugh, additional, Cornet, Céline, additional, Coutris, Pierre, additional, Couvreux, Fleur, additional, Crewell, Susanne, additional, Cronin, Timothy Wallace, additional, Cui, Zhiqiang, additional, Cuypers, Yannis, additional, Daley, Alton, additional, Damerell, Gillian Mary, additional, Dauhut, Thibaut, additional, Deneke, Hartwig M, additional, Desbios, Jean-Philippe, additional, Dörner, Steffen, additional, Donner, Sebastian, additional, Douet, Vincent, additional, Drushka, Kyla, additional, Dütsch, Marina, additional, Ehrlich, André, additional, Emanual, Kerry, additional, Emmanouilidis, Alexandros, additional, Etienne, Jean-Claude, additional, Etienne-Leblanc, Sheryl, additional, Faure, Ghislain, additional, Feingold, Graham, additional, Ferrero, Luca, additional, Fix, Andreas, additional, Flamant, Cyrille, additional, Flatau, Piotr J., additional, Foltz, Gregory R., additional, Forster, Linda, additional, Furtuna, Iulian, additional, Gadian, Alan, additional, Galewsky, Joseph, additional, Gallagher, Martin, additional, Gallimore, Peter, additional, Gaston, Cassandra J., additional, Gentemann, Chelle, additional, Geyskens, Nicolas, additional, Giez, Andreas, additional, Gollop, John, additional, Gouirand, Isabelle, additional, Gourbeyre, Christophe, additional, de Graaf, Dörte, additional, de Groot, Geiske E., additional, Grosz, Robert, additional, Güttler, Johannes, additional, Gutleben, Manuel, additional, Hall, Kashawn, additional, Harris, George, additional, Helfer, Kevin Christopher, additional, Henze, Dean, additional, Herbert, Calvert, additional, Holanda, Bruna, additional, Ibanez-Landeta, Antonio, additional, Intrieri, Janet M., additional, Iyer, Suneil, additional, Julien, Fabrice, additional, Kalesse, Heike, additional, Kazil, Jan, additional, Kellman, Alexander, additional, Kidane, Abiel T., additional, Kirchner, Ulrike, additional, Klingebiel, Marcus, additional, Körner, Mareike, additional, Kremper, Leslie Ann, additional, Kretzschmar, Jan, additional, Krüger, Ovid, additional, Kumala, Wojciech, additional, Kurz, Armin, additional, L'Hégaret, Pierre, additional, Labaste, Matthieu, additional, Lachlan-Cope, Tom A., additional, Laing, Arlene, additional, Landschützer, Peter, additional, Lang, Theresa, additional, Lange Vega, Diego, additional, Lange, Ingo, additional, Laplace, Clément, additional, Lavik, Gaute, additional, LAXENAIRE, Rémi, additional, Le Bihan, Caroline, additional, Leandro, Mason, additional, Lefèvre, Nathalie, additional, Lena, Marius, additional, Leschow, Donald, additional, Li, Qiang, additional, Lloyd, Gary, additional, Los, Sebastian, additional, Losi, Niccolò, additional, Lovell, Oscar, additional, Luneau, Christopher, additional, Makuch, Przemysław, additional, Malinowski, Szymon P, additional, Manta, Gaston, additional, Marinou, Eleni, additional, Marsden, Nicholas, additional, Masson, Sebastien, additional, Maury, Nicolas, additional, Mayer, Bernhard, additional, Mayers-Als, Margarette, additional, Mazel, Christophe, additional, McGeary, Wayne, additional, McWilliams, James C., additional, Mech, Mario, additional, Mehlmann, Melina, additional, Meroni, Agostino Niyonkuru, additional, Mieslinger, Theresa, additional, Minikin, Andreas, additional, Minnett, Peter, additional, Möller, Gregor, additional, Morfa Avalos, Yanmichel, additional, Muller, Caroline, additional, Musat, Ionela, additional, Napoli, Anna, additional, Neuberger, Almuth, additional, Noisel, Christophe, additional, Noone, David C, additional, Nordsiek, Freja, additional, Nowak, Jakub L, additional, Oswald, Lothar, additional, Parker, Douglas J., additional, Peck, Carolyn, additional, Person, Renaud, additional, Philippi, Miriam, additional, Plueddemann, Albert J., additional, Pöhlker, Christopher, additional, Pörtge, Veronika, additional, Pöschl, Ulrich, additional, Pologne, Lawrence, additional, Posyniak, Michal, additional, Prange, Marc, additional, Quiñones Meléndez, Estefanía, additional, Radtke, Jule, additional, Ramage, Karim, additional, Reimann, Jens, additional, Renault, Lionel, additional, Reus, Klaus, additional, Reyes, Ashford, additional, Ribbe, Joachim, additional, Ringel, Maximilian, additional, Ritschel, Markus, additional, Rocha, Cesar Barbedo, additional, Rochetin, Nicolas, additional, Röttenbacher, Johannes, additional, Rollo, Callum, additional, Royer, Haley, additional, Sadoulet, Pauline, additional, Saffin, Leo, additional, Sandiford, Sanola, additional, Sandu, Irina, additional, Schäfer, Michael, additional, Schemann, Vera, additional, Schirmacher, Imke, additional, Schlenczek, Oliver, additional, Schmidt, Jerome, additional, Schröder, Marcel, additional, Schwarzenboeck, Alfons, additional, Sealy, Andrea, additional, Senff, Christoph J, additional, Serikov, Ilya, additional, Shohan, Samkeyat, additional, Siddle, Elizabeth, additional, Smirnov, Alexander, additional, Späth, Florian, additional, Spooner, Branden, additional, Stolla, M. Katharina, additional, Szkółka, Wojciech, additional, de Szoeke, Simon P., additional, Tarot, Stéphane, additional, Tetoni, Eleni, additional, Thompson, Elizabeth J, additional, Thomson, Jim, additional, Tomassini, Lorenzo, additional, Totems, Julien, additional, Ubele, Alma Anna, additional, Villiger, Leonie, additional, von Arx, Jan, additional, Wagner, Thomas, additional, Walther, Andi, additional, Webber, Benjamin G. M., additional, Wendisch, Manfred, additional, Whitehall, Shanice, additional, Wiltshire, Anton, additional, Wing, Allison A., additional, Wirth, Martin, additional, Wiskandt, Jonathan, additional, Wolf, Kevin, additional, Worbes, Ludwig, additional, Wright, Ethan, additional, Wulfmeyer, Volker, additional, Young, Shanea, additional, Zhang, Chidong, additional, Zhang, Dongxiao, additional, Ziemen, Florian, additional, Zinner, Tobias, additional, and Zöger, Martin, additional

Published
2020
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29. Deployment of the C-band radar Poldirad on Barbados during EUREC4A.

Author

Hagen, Martin, Ewald, Florian, Groß, Silke, Oswald, Lothar, Farrell, David A., Forde, Marvin, Gutleben, Manuel, Heumos, Johann, Reimann, Jens, Tetoni, Eleni, Marinou, Eleni, Möller, Gregor, Kiemle, Christoph, Li, Qiang, Chewitt-Lucas, Rebecca, Daley, Alton, Grant, Delando, and Hall, Kashawn

Subjects
BARBADOS
Abstract

The German polarimetric C-band weather radar Poldirad (Polarization Diversity Radar) was deployed for the international field campaign EUREC4A (ElUcidating the RolE of Cloud-Circulation Coupling in ClimAte) on the island of Barbados. Poldirad was operated on Barbados from February until August 2020. Focus of the installation was monitoring clouds and precipitation in the trade wind region east of Barbados. Different scanning modes were used with a temporal sequence of 5 minutes and a maximum range of 375 km. In addition to built-in quality control performed by the radar signal processor, it was found that the copoloar correlation coefficient ρHV can be used to remove contamination of radar products by sea clutter. Radar images were available in real-time for all campaign participants and onboard of research aircraft. Examples of mesoscale precipitation patterns, rain rate accumulation, diurnal cycle, and vertical distribution are given to show the potential of the radar measurements for further studies on the life cycle of precipitating shallow cumulus clouds and other related aspects. Poldirad data from the EUREC4A campaign are available on the EUREC4A AERIS database: https://doi.org/10.25326/218 (Hagen et al., 2021a) for raw data and https://doi.org/10.25326/217 (Hagen et al., 2021b) for gridded data. [ABSTRACT FROM AUTHOR]

Published
2021
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30. Overview: Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes.

Author

Trömel, Silke, Simmer, Clemens, Blahak, Ulrich, Blanke, Armin, Ewald, Florian, Frech, Michael, Gergely, Mathias, Hagen, Martin, Hörnig, Sabine, Janjic, Tijana, Kalesse, Heike, Kneifel, Stefan, Knote, Christoph, Mendrok, Jana, Moser, Manuel, Möller, Gregor, Mühlbauer, Kai, Myagkov, Alexander, Pejcic, Velibor, and Seifert, Patric

Abstract

Cloud and precipitation processes are still the main source of uncertainties in numerical weather prediction and climate change projections. The Priority Program "Polarimetric Radar Observations meet Atmospheric Modelling (PROM)", funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), is guided by the hypothesis, that many uncertainties relate to the lack of observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Such observations can, however, nowadays be provided e.g. by the recently installed dual-polarization C band weather radar network of the German national meteorological service in synergy with cloud radars and other instruments at German supersites and similar national networks increasingly available worldwide. While polarimetric radars potentially provide valuable in-cloud information e.g. on hydrometeor type, quantity, and microphysical cloud and precipitation processes, and atmospheric models employ increasingly higher moment microphysical modules, still considerable knowledge gaps exist in the interpretation of the observations and large uncertainties in the optimal microphysics model process formulations. PROM is a coordinated interdisciplinary effort to intensify the use of polarimetric radar observations in data assimilation, which requires a thorough evaluation and improvement of parametrizations of moist processes in atmospheric models. As an overview article of the inter journal special issue "Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes", it outlines the knowledge achieved in PROM during the past two years and gives perspectives for the next four years. [ABSTRACT FROM AUTHOR]

Published
2021
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36. Inter-technique validation of tropospheric slant total delays

Author

Kačmařík, Michal, primary, Douša, Jan, additional, Dick, Galina, additional, Zus, Florian, additional, Brenot, Hugues, additional, Möller, Gregor, additional, Pottiaux, Eric, additional, Kapłon, Jan, additional, Hordyniec, Paweł, additional, Václavovic, Pavel, additional, and Morel, Laurent, additional

Published
2017
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37. Assimilation of GNSS tomography products into WRF using radio occultation data assimilation operator.

Author

Hanna, Natalia, Trzcina, Estera, Möller, Gregor, Rohm, Witold, and Weber, Robert

Subjects
GLOBAL Positioning System, NUMERICAL weather forecasting, SEISMIC tomography, METEOROLOGICAL research, ATMOSPHERIC water vapor measurement, WEATHER forecasting, TOMOGRAPHY
Abstract

From Global Navigation Satellite Systems (GNSS) signals, accurate and high-frequency atmospheric parameters can be determined in all-weather conditions. GNSS tomography is a novel technique that takes advantage of these parameters, especially of slant troposphere observations between GNSS receivers and satellites, traces these signals through a 3D grid of voxels and estimates by an inversion process the refractivity of the water vapour content within each voxel. In the last years, the GNSS tomography development focused on numerical methods to stabilize the solution, which has been achieved to a great extent. Currently, we are facing new challenges and possibilities in the application of GNSS tomography in numerical weather forecasting - the main research objective of this paper. In the first instance, refractivity fields were estimated using two different GNSS tomography models (TUW, WUELS), which cover the area of Central Europe during the period of 29 May-14 June 2013, when heavy precipitation events were observed. For both models, Slant Wet Delays (SWD) were calculated based on estimates of Zenith Total Delay (ZTD) and horizontal gradients, provided for 72 GNSS sites by Geodetic Observatory Pecny (GOP). In total, three sets of SWD observations were tested (set0 without compensation for hydrostatic anisotropic effects, set1 with compensation of this effect, set2 cleaned by wet delays outside the inner voxel model). The GNSS tomography outputs have been assimilated into the nested (12- and 36-km horizontal resolution) Weather Research and Forecasting (WRF) model, using its three-dimensional variational data assimilation (WRFDA 3DVar) system, in particular its radio occultation observations operator (GPSREF). As only total refractivity is assimilated in GPSREF, it was calculated as the sum of the hydrostatic part derived from the ALADIN-CZ model and the wet part from the GNSS tomography. We compared the results of the GNSS tomography data assimilation to the radiosonde (RS) observations. The validation shows the improvement in the weather forecasting of relative humidity (bias, standard deviation) and temperature (standard deviation) during heavy precipitation events. Future improvements to the assimilation method are also discussed. [ABSTRACT FROM AUTHOR]

Published
2019
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38. Cross-validation of GPS tomography models and methodological improvements using CORS network.

Author

Brenot, Hugues, Champollion, Cédric, Rohm, Witold, Tondaś, Damian, Kačmařík, Michal, Möller, Gregor, Sá, André, Rapant, Lukas, Biondi, Riccardo, and Manning, Toby

Subjects
TOMOGRAPHY, WEATHER
Abstract

Using data from the Continuously Operating Reference Stations (CORS), recorded in March 2010 during severe weather in the Victoria State, in southern Australia, sensitivity and statistical results of GPS tomography retrievals (water vapour density and wet refractivity) from 5 models have been tested and verified – considering independent observations from radiosonde and radio occultation profiles. The impact of initial conditions, associated with different time-convergence of tomography inversion, can reduce the normalised RMS of the tomography solution with respect to radiosonde estimates by a multiple (up to more than 3). Thereby it is illustrated that the quality of the apriori data in combination with iterative processing is critical, independently of the choice of the tomography model. However, the use of data stacking and pseudo-slant observations can significantly improve the quality of the retrievals, due to a better geometrical distribution and a better coverage of mid- and low-tropospheric parts. Besides, the impact of the uncertainty of GPS observations has been investigated, showing the interest of using several sets of data input to evaluate tomography retrievals in comparison to independent external measurements, and to estimate simultaneously the quality of NWP outputs. Finally, a comparison of our multi-model tomography with numerical weather prediction from ACCESS-A model shows the relevant use of tomography retrieval to improve the understanding of such severe weather conditions, especially about the initiation of the deep convection. [ABSTRACT FROM AUTHOR]

Published
2018
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40. Atmospheric bending effects in GNSS tomography.

Author

Möller, Gregor and Landskron, Daniel

Subjects
*GLOBAL Positioning System, *ATMOSPHERIC acoustics
Abstract

In GNSS tomography, precise information about the tropospheric water vapor distribution is derived from integral measurements like GNSS slant wet delays (SWDs). Therefore, the functional relation between observations and unknowns, i.e. the signal paths have to be accurately known for each station-satellite pair involved. Since GNSS signals are prone to atmospheric bending effects, a straight line assumption is not sufficient for elevation angles <15°. Thus, in the following, a mixed 2D piecewise linear ray-tracing approach is introduced and possible error sources in reconstruction of the bended signal paths are analyzed in more detail. Especially, if low elevation observations (ε<10°) are considered, unmodeled bending effects can introduce a systematic error of up to 10-20ppm, on average of 1-2ppm into the tomography solution. Thereby, the ray-tracing approach itself but primarily the quality of the a priori field has a significant impact on the reconstruction quality. In order to overcome possible limitations in the a priori field, an iterative tomography processing strategy is applied. Further, a bending model helps to reduce the number of processing steps by up to 85%. In consequence, the developed mixed ray-tracing approach allows not only for a correct treatment of low elevation observations but is also fast and applicable for near real-time applications. [ABSTRACT FROM AUTHOR]

Published
2018
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41. Inter-technique validation of tropospheric slant total delays.

Author

Kaˇcmaˇrík, Michal, Douša, Jan, Dick, Galina, Zus, Florian, Brenot, Hugues, Möller, Gregor, Pottiaux, Eric, Kapłon, Jan, Hordyniec, Paweł, Václavovic, Pavel, and Morel, Laurent

Subjects
TROPOSPHERE, GLOBAL Positioning System, NUMERICAL weather forecasting, ATMOSPHERIC water vapor measurement, STANDARD deviations
Abstract

An extensive validation of line-of-sight tropospheric slant total delays (STD) from Global Navigation Satellite Systems (GNSS), ray tracing in numerical weather prediction model (NWM) fields and microwave water vapour radiometer (WVR) is presented. Ten GNSS reference stations, including collocated sites, and almost 2 months of data from 2013, including severe weather events were used for comparison. Seven institutions delivered their STDs based on GNSS observations processed using 5 software programs and 11 strategies enabling to compare rather different solutions and to assess the impact of several aspects of the processing strategy. STDs from NWM ray tracing came from three institutions using three different NWMs and ray-tracing software. Inter-techniques evaluations demonstrated a good mutual agreement of various GNSS STD solutions compared to NWM and WVR STDs. The mean bias among GNSS solutions not considering post-fit residuals in STDs was -0.6 mm for STDs scaled in the zenith direction and the mean standard deviation was 3.7 mm. Standard deviations of comparisons between GNSS and NWM ray-tracing solutions were typically 10 mm ± 2 mm (scaled in the zenith direction), depending on the NWM model and the GNSS station. Comparing GNSS versus WVR STDs reached standard deviations of 12 mm ± 2 mm also scaled in the zenith direction. Impacts of raw GNSS post-fit residuals and cleaned residuals on optimal reconstructing of GNSS STDs were evaluated at intertechnique comparison and for GNSS at collocated sites. The use of raw post-fit residuals is not generally recommended as they might contain strong systematic effects, as demonstrated in the case of station LDB0. Simplified STDs reconstructed only from estimated GNSS tropospheric parameters, i.e. without applying post-fit residuals, performed the best in all the comparisons; however, it obviously missed part of tropospheric signals due to non-linear temporal and spatial variations in the troposphere. Although the post-fit residuals cleaned of visible systematic errors generally showed a slightly worse performance, they contained significant tropospheric signal on top of the simplified model. They are thus recommended for the reconstruction of STDs, particularly during high variability in the troposphere. Cleaned residuals also showed a stable performance during ordinary days while containing promising information about the troposphere at low-elevation angles. [ABSTRACT FROM AUTHOR]

Published
2017
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45. Cross-Comparison and Methodological Improvement in GPS Tomography.

Author

Brenot, Hugues, Rohm, Witold, Kačmařík, Michal, Möller, Gregor, Sá, André, Tondaś, Damian, Rapant, Lukas, Biondi, Riccardo, Manning, Toby, and Champollion, Cédric

Subjects
SEISMIC tomography, TOMOGRAPHY, NUMERICAL weather forecasting, SEVERE storms, WEATHER forecasting, WEATHER
Abstract

GPS tomography has been investigated since 2000 as an attractive tool for retrieving the 3D field of water vapour and wet refractivity. However, this observational technique still remains a challenging task that requires improvement of its methodology. This was the purpose of this study, and for this, GPS data from the Australian Continuously Operating Research Station (CORS) network during a severe weather event were used. Sensitivity tests and statistical cross-comparisons of tomography retrievals with independent observations from radiosonde and radio-occultation profiles showed improved results using the presented methodology. The initial conditions, which were associated with different time-convergence of tomography inversion, play a critical role in GPS tomography. The best strategy can reduce the normalised root mean square (RMS) of the tomography solution by more than 3 with respect to radiosonde estimates. Data stacking and pseudo-slant observations can also significantly improve tomography retrievals with respect to non-stacked solutions. A normalised RMS improvement up to 17% in the 0–8 km layer was found by using 30 min data stacking, and RMS values were divided by 5 for all the layers by using pseudo-observations. This result was due to a better geometrical distribution of mid- and low-tropospheric parts (a 30% coverage improvement). Our study of the impact of the uncertainty of GPS observations shows that there is an interest in evaluating tomography retrievals in comparison to independent external measurements and in estimating simultaneously the quality of weather forecasts. Finally, a comparison of multi-model tomography with numerical weather prediction shows the relevant use of tomography retrievals to improving the understanding of such severe weather conditions. [ABSTRACT FROM AUTHOR]

Published
2020
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46. Combination of GNSS tomography and GNSS radio occultation to establish wet refractivity fields.

Author

Hanna, Natalia, Möller, Gregor, and Weber, Robert

Subjects
*ATMOSPHERIC water vapor, *DOPPLER effect, *LOW earth orbit satellites, *TOMOGRAPHY, *SURFACE of the earth, *GRID cells
Abstract

The GNSS tomography is a novel technique which uses the GNSS data for resolving a temporal and spatial field of the atmospheric water vapour above a network of receivers. In the GNSS tomography process, the integrated information about the amount of water vapour between a GNSS satellite and each single GNSS ground station, i.e., Slant Total Delay (STD) observations, are required. The tomography works on a spatial grid and tries to spread the integral slant delays on the different grid cells. The state-of-the-art studies are focused on the development of the GNSS tomography solution. Recent research shows that the GNSS tomography results can be improved by an introduction of additional observations, such as vertical profiles of refractivity, into the equation system.The vertical profile of wet refractivity can be derived, e.g., from GNSS radio occultation (RO) data. The radio occultation is a remote sensing technique for measuring atmospheric properties using GNSS signals. It provides high-resolution vertical soundings that have low sensitivity to clouds and precipitation, over both land and ocean. The space-based GNSS RO technique measures the excess phase delay and Doppler shift of a GNSS radio signal which results from the atmospheric refraction of the signal along the path between the transmitting GNSS satellite and receiver in Low Earth Orbit (LEO). Because of the vertical and temporal resolution, and high precision and accuracy of the RO technique, introducing the wet refractivity profiles derived from the radio occultation data can considerably improve the tomography solution.In this study, the potential of the use of vertical profiles of refractivity derived from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) in the 'ATom' GNSS tomography software has been investigated. The COSMIC data are of good quality and penetrate the Earth's surface very close; 70% - 90% of the soundings reach to within 1 km of the surface on a global basis. The GNSS tomography in the domain of Central Europe (Austria, south Germany, south-west Poland), using STD observations of 174 GNSS reference stations, in two weeks from September 1, 2017, to September 15, 2017, has been performed. In this period, 6 GNSS RO events occurred in the domain area. The RO observations have been added to the equation system as constraints. The advantages and benefits of the combination of the GNSS tomography and RO technique for the estimation of atmospheric wet refractivity fields are presented. [ABSTRACT FROM AUTHOR]

Published
2019

47. Cross-Comparison and Methodological Improvement in GPS Tomography

Author

Brenot, Hugues, Rohm, Witold, Kačmařík, Michal, Möller, Gregor, Sá, André, Tondaś, Damian, Rapant, Lukas, Biondi, Riccardo, Manning, Toby, and Champollion, Cédric

Subjects
GPS tomography, data stacking, 13. Climate action, severe weather, a priori condition, pseudo-slant observations, methodological improvement
Abstract

GPS tomography has been investigated since 2000 as an attractive tool for retrieving the 3D field of water vapour and wet refractivity. However, this observational technique still remains a challenging task that requires improvement of its methodology. This was the purpose of this study, and for this, GPS data from the Australian Continuously Operating Research Station (CORS) network during a severe weather event were used. Sensitivity tests and statistical cross-comparisons of tomography retrievals with independent observations from radiosonde and radio-occultation profiles showed improved results using the presented methodology. The initial conditions, which were associated with different time-convergence of tomography inversion, play a critical role in GPS tomography. The best strategy can reduce the normalised root mean square (RMS) of the tomography solution by more than 3 with respect to radiosonde estimates. Data stacking and pseudo-slant observations can also significantly improve tomography retrievals with respect to non-stacked solutions. A normalised RMS improvement up to 17% in the 0–8 km layer was found by using 30 min data stacking, and RMS values were divided by 5 for all the layers by using pseudo-observations. This result was due to a better geometrical distribution of mid- and low-tropospheric parts (a 30% coverage improvement). Our study of the impact of the uncertainty of GPS observations shows that there is an interest in evaluating tomography retrievals in comparison to independent external measurements and in estimating simultaneously the quality of weather forecasts. Finally, a comparison of multi-model tomography with numerical weather prediction shows the relevant use of tomography retrievals to improving the understanding of such severe weather conditions., Remote Sensing, 12 (1), ISSN:2072-4292

48. Elegie/ oder Trauer-Gedicht/ über den erschrecklichen und grossen Brand welcher ... Goerlitz und sonderlich darinnen ... weitberuffennen Haupt-Kirche zu S. Peter u. Paul/ am XIX. Mertens des MDC XCI. Jahrs ... Bey der Gregorius Feyer gemeldeten Jahres auf dem Görlitzischen Helicon

Author

Schultess, Georg, Melde, Johann Heinrich, Möller, Gregor, Preibius, Christoph, Meyrich, Elias, Hassfurth, Johann Christoph, Schultess, Georg, Melde, Johann Heinrich, Möller, Gregor, Preibius, Christoph, Meyrich, Elias, and Hassfurth, Johann Christoph

Abstract

abgesungenvon Johann Christoph Haßfurthen/ von Lodenau aus der Ober-Lausitz, Schlüsselseiten aus dem Exemplar der ULB Halle: Pon Yb 1072, QK

49. Elegie/ oder Trauer-Gedicht/ über den erschrecklichen und grossen Brand welcher ... Goerlitz und sonderlich darinnen ... weitberuffennen Haupt-Kirche zu S. Peter u. Paul/ am XIX. Mertens des MDC XCI. Jahrs ... Bey der Gregorius Feyer gemeldeten Jahres auf dem Görlitzischen Helicon

Author

Schultess, Georg, Melde, Johann Heinrich, Möller, Gregor, Preibius, Christoph, Meyrich, Elias, Hassfurth, Johann Christoph, Schultess, Georg, Melde, Johann Heinrich, Möller, Gregor, Preibius, Christoph, Meyrich, Elias, and Hassfurth, Johann Christoph

Abstract

abgesungenvon Johann Christoph Haßfurthen/ von Lodenau aus der Ober-Lausitz, Schlüsselseiten aus dem Exemplar der ULB Halle: Pon Yb 1072, QK

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