Articles | Volume 9, issue 11
https://doi.org/10.5194/amt-9-5385-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/amt-9-5385-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
| 
08 Nov 2016
Review article |
| 08 Nov 2016
Review of the state of the art and future prospects of the ground-based GNSS meteorology in Europe
Guergana Guerova
CORRESPONDING AUTHOR
Department Meteorology and Geophysics, Sofia University St. Kliment Ohridski, 1164 Sofia, Bulgaria
Jonathan Jones
Met Office, EX1 3PB Exeter, UK
Jan Douša
New Technologies for the Information Society, Geodetic Observatory Pecný, RIGTC, 25066 Zdiby, Czech Republic
Galina Dick
Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
Siebren de Haan
Koninklijk Nederlands Meteorologisch Instituut, 3732 GK De Bilt, the Netherlands
Eric Pottiaux
Royal Observatory of Belgium, 1180 Brussels, Belgium
Olivier Bock
Institut National de l'Information Géographique et Forestière, 94160 Saint-Mande, France
Rosa Pacione
E-geos s.p.a ASI/CGS, 75100 Matera, Italy
Gunnar Elgered
Department of Earth and Space Sciences, Chalmers University of Technology, 43992 Onsala, Sweden
Henrik Vedel
Danish Meteorological Institute, 2100 Copenhagen, Denmark
Michael Bender
Deutscher Wetterdienst, 63067 Offenbach, Germany
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The gradients estimated from multi-GNSS data were compared to WVR data. A better agreement is obtained when using WVR data with a smaller value of liquid water content. A weak constraint in GNSS data processing may be desirable for applications with a higher tolerance for formal errors but a greater focus on tracking the variability of water vapour. The averaged GNSS gradients can significantly reduce the random noise which can be used to obtain a more reliable variability of the water vapour.
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Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
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This manscript describes the operational method of extracting meteorological information from all airborne aircraft in the European airspace every 20 seconds to 1 minute. The methodology is described and the quality of the wind and temperature observations are evaluated against radiosonde observations.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
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Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
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Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Olivier Bock, Pierre Bosser, and Carl Mears
Atmos. Meas. Tech., 15, 5643–5665, https://doi.org/10.5194/amt-15-5643-2022, https://doi.org/10.5194/amt-15-5643-2022, 2022
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Integrated water vapour measurements are often compared for the calibration and validation of instruments or techniques. Measurements made at different altitudes must be corrected to account for the vertical variation of water vapour. This paper shows that the widely used empirical correction model has severe limitations that are overcome using the proposed model. The method is applied to the inter-comparison of GPS and satellite microwave radiometer data in a tropical mountainous area.
Siebren de Haan, Paul M. A. de Jong, and Jitze van der Meulen
Atmos. Meas. Tech., 15, 811–818, https://doi.org/10.5194/amt-15-811-2022, https://doi.org/10.5194/amt-15-811-2022, 2022
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AMDAR temperatures suffer from a bias, which can be related to a difference in the timing of height and measurement and to internal corrections applied to pressure altitude. Based on NWP model temperature data, combined with Mach number and true airspeed, we could estimate corrections. Comparing corrected temperatures with (independent) radiosonde observations demonstrates a reduction in the bias, from 0.5 K to around zero, and standard deviation, of almost 10 %.
Karina Wilgan, Galina Dick, Florian Zus, and Jens Wickert
Atmos. Meas. Tech., 15, 21–39, https://doi.org/10.5194/amt-15-21-2022, https://doi.org/10.5194/amt-15-21-2022, 2022
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The assimilation of GNSS data in weather models has a positive impact on the forecasts. The impact is still limited due to using only the GPS zenith direction parameters. We calculate and validate more advanced tropospheric products from three satellite systems: the US American GPS, Russian GLONASS and European Galileo. The quality of all the solutions is comparable; however, combining more GNSS systems enhances the observations' geometry and improves the quality of the weather forecasts.
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.
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.
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).
Olivier Bock, Pierre Bosser, Cyrille Flamant, Erik Doerflinger, Friedhelm Jansen, Romain Fages, Sandrine Bony, and Sabrina Schnitt
Earth Syst. Sci. Data, 13, 2407–2436, https://doi.org/10.5194/essd-13-2407-2021, https://doi.org/10.5194/essd-13-2407-2021, 2021
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Measurements from a network of Global Navigation Satellite System (GNSS) receivers operated from the eastern Caribbean islands are used to monitor the total water vapour content in the atmosphere during the EUREC4A field campaign. These data help describe the moisture environment of mesoscale cloud patterns in the trade winds with high temporal sampling. They are also useful to assess the accuracy of collocated radiosonde measurements and numerical weather model reanalyses.
Pierre Bosser, Olivier Bock, Cyrille Flamant, Sandrine Bony, and Sabrina Speich
Earth Syst. Sci. Data, 13, 1499–1517, https://doi.org/10.5194/essd-13-1499-2021, https://doi.org/10.5194/essd-13-1499-2021, 2021
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In the framework of the EUREC4A campaign, water vapour measurements were retrieved over the tropical west Atlantic Ocean from GNSS data acquired from three research vessels (R/Vs Atalante, Maria S. Merian and Meteor). The retrievals from R/Vs Atalante and Meteor are shown to be of high quality unlike the results for the R/V Maria S. Merian. These ship-borne retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign.
Pierre Bosser and Olivier Bock
Adv. Geosci., 55, 13–22, https://doi.org/10.5194/adgeo-55-13-2021, https://doi.org/10.5194/adgeo-55-13-2021, 2021
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For the documentation of time and space variations of water vapor in atmosphere during the Nawdex campaign (fall 2016), a ground network of more than 1200 continuously operation reference GNSS stations has been analyzed. This network spreads from Caribbeans to Morocco through Greenland. This study presents the retrieval of Integrated Water Vapor content from GNSS measurements and their use in the evaluation of the European Centre for Medium-Range Weather Forecasts reanalyses ERAI and ERA5.
Samuel Nahmani, Olivier Bock, and Françoise Guichard
Atmos. Chem. Phys., 19, 9541–9561, https://doi.org/10.5194/acp-19-9541-2019, https://doi.org/10.5194/acp-19-9541-2019, 2019
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A mesoscale convective system (MCS) is a cloud system that occurs in connection with an ensemble of thunderstorms and produces a contiguous precipitation area of the order of 100 km or more. Numerous questions related to MCSs remain poorly answered (e.g., their life cycle, and interactions between physical processes and atmospheric circulations). This work shows how a GPS technique can provide relevant and complementary information on MCSs passing over or in the vicinity of observation stations.
Olivier Bock and Ana C. Parracho
Atmos. Chem. Phys., 19, 9453–9468, https://doi.org/10.5194/acp-19-9453-2019, https://doi.org/10.5194/acp-19-9453-2019, 2019
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We examine the consistency of global IWV data from ERA-Interim reanalysis and 16 years of GPS observations. Representativeness differences are found to be a dominant error source, with a strong dependence on geographic, topographic, and climatic features, which explain both average and extreme differences. A methodology for reducing the representativeness errors and detecting the extreme, outlying, cases is discussed.
Gunnar Elgered, Tong Ning, Peter Forkman, and Rüdiger Haas
Atmos. Meas. Tech., 12, 3805–3823, https://doi.org/10.5194/amt-12-3805-2019, https://doi.org/10.5194/amt-12-3805-2019, 2019
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Within the EU COST Action ES1206 we have studied the horizontal variability of the atmosphere using signals from GPS satellites, distant quasars, and a microwave radiometer. We find a consistent picture: horizontal variability over timescales of months are mainly due to atmospheric pressure, whereas water vapour is the main cause of variations over times from minutes to hours. An understanding of these variations helps to improve the accuracy of GPS applications in both geodesy and meteorology.
Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, Olivier Caumont, Alexis Doerenbecher, Eric Wattrelot, Patrick Moll, Hervé Bénichou, Dominique Puech, Olivier Bock, Pierre Bosser, Patrick Chazette, Cyrille Flamant, Paolo Di Girolamo, Evelyne Richard, and Frédérique Saïd
Geosci. Model Dev., 12, 2657–2678, https://doi.org/10.5194/gmd-12-2657-2019, https://doi.org/10.5194/gmd-12-2657-2019, 2019
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The AROME-WMED (western Mediterranean) model is a dedicated version of the mesoscale Numerical Weather Prediction AROME-France model that ran in real time during the first special observation period of HyMeX. Two reanalyses were performed after the campaign. This paper depicts the main differences between the real-time version and the benefits brought by both HyMeX reanalyses. The second reanalysis is found to be closer to observations than the previous AROME-WMED analyses.
Michal Kačmařík, Jan Douša, Florian Zus, Pavel Václavovic, Kyriakos Balidakis, Galina Dick, and Jens Wickert
Ann. Geophys., 37, 429–446, https://doi.org/10.5194/angeo-37-429-2019, https://doi.org/10.5194/angeo-37-429-2019, 2019
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We provide an analysis of processing setting impacts on tropospheric gradients estimated from GNSS observation processing. These tropospheric gradients are related to water vapour distribution in the troposphere and therefore can be helpful in meteorological applications.
Sophie Bastin, Philippe Drobinski, Marjolaine Chiriaco, Olivier Bock, Romain Roehrig, Clemente Gallardo, Dario Conte, Marta Domínguez Alonso, Laurent Li, Piero Lionello, and Ana C. Parracho
Atmos. Chem. Phys., 19, 1471–1490, https://doi.org/10.5194/acp-19-1471-2019, https://doi.org/10.5194/acp-19-1471-2019, 2019
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This paper uses colocated observations of temperature, precipitation and humidity to investigate the triggering of precipitation. It shows that there is a critical value of humidity above which precipitation picks up. This critical value depends on T and varies spatially. It also analyses how this dependency is reproduced in regional climate simulations over Europe. Models with too little and too light precipitation have both lower critical value of humidity and higher probability to exceed it.
Julie Berckmans, Roeland Van Malderen, Eric Pottiaux, Rosa Pacione, and Rafiq Hamdi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1097, https://doi.org/10.5194/acp-2018-1097, 2018
Preprint withdrawn
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The use of ground-based observations is suitable for the assessment of atmospheric water vapour in climate models. We used water vapour observations from 100 European sites to evaluate two models: a reanalysis product and a regional climate model. The results reveal patterns in the water vapour distribution both in time and space that are relevant as water vapour plays a key role in the feedback process of a changing climate.
Roeland Van Malderen, Eric Pottiaux, Gintautas Stankunavicius, Steffen Beirle, Thomas Wagner, Hugues Brenot, and Carine Bruyninx
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1170, https://doi.org/10.5194/acp-2018-1170, 2018
Revised manuscript not accepted
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The study investigates the long-term time variability of the integrated water vapour retrieved by different techniques (GPS, UV/VIS satellites and numerical weather prediction reanalyses) for a global dataset of almost 120 sites and for the time period 1995–2010. A stepwise multiple linear regression technique is applied to ascribe the time variability of integrated water vapour to surface measurements at the sites, but also using teleconnection patterns or climate/oceanic indices.
Ana C. Parracho, Olivier Bock, and Sophie Bastin
Atmos. Chem. Phys., 18, 16213–16237, https://doi.org/10.5194/acp-18-16213-2018, https://doi.org/10.5194/acp-18-16213-2018, 2018
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Integrated water vapour from GPS observations and two modern atmospheric reanalyses were compared for 1995–2010. Means, variability and trend signs were in general good agreement. Regions and GPS stations with poor agreement were investigated further. Representativeness issues, uncertainties in reanalyses, and inhomogeneities in GPS were evidenced. Reanalyses were compared for an extended period, and a focus on north Africa and Australia highlighted the impact of dynamics on water vapour trends.
Tong Ning and Gunnar Elgered
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-279, https://doi.org/10.5194/amt-2018-279, 2018
Preprint withdrawn
Ermanno Fionda, Maria Cadeddu, Vinia Mattioli, and Rosa Pacione
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-161, https://doi.org/10.5194/amt-2018-161, 2018
Publication in AMT not foreseen
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The purpose of the present study is to contribute to the understanding of the differences in integrated water vapour (IWV) measurements between Global Positioning System and other observing systems to characterize the uncertainties associated with GPS measurements in Finland. Results show that the GPS agrees with other instruments within 0.5 kg/m2 during winter. During summer the differences increase to 1.5 kg/m2 due to the spatial variability of water vapor in the observation region.
Dunya Alraddawi, Alain Sarkissian, Philippe Keckhut, Olivier Bock, Stefan Noël, Slimane Bekki, Abdenour Irbah, Mustapha Meftah, and Chantal Claud
Atmos. Meas. Tech., 11, 2949–2965, https://doi.org/10.5194/amt-11-2949-2018, https://doi.org/10.5194/amt-11-2949-2018, 2018
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The current study provides intercomparisons of various water vapour measurements in the Arctic. It compares ground-based GPS observations with satellite measurements in the infrared (IR), near-infrared (NIR) and visible (VIS) through a specific method allowing us to quantify their uncertainties and limits.
Unlike IR, satellite observations in NIR and VIS bands are mostly sensible to cloud cover during summer and to albedo variability over canopy or polluted snow-covered surfaces in winter.
Katarzyna Stepniak, Olivier Bock, and Pawel Wielgosz
Atmos. Meas. Tech., 11, 1347–1361, https://doi.org/10.5194/amt-11-1347-2018, https://doi.org/10.5194/amt-11-1347-2018, 2018
Monica Campanelli, Alessandra Mascitelli, Paolo Sanò, Henri Diémoz, Victor Estellés, Stefano Federico, Anna Maria Iannarelli, Francesca Fratarcangeli, Augusto Mazzoni, Eugenio Realini, Mattia Crespi, Olivier Bock, Jose A. Martínez-Lozano, and Stefano Dietrich
Atmos. Meas. Tech., 11, 81–94, https://doi.org/10.5194/amt-11-81-2018, https://doi.org/10.5194/amt-11-81-2018, 2018
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The estimation of precipitable water vapour (W) content is of great interest in both meteorological and climatological studies. Sun photometers allowed the development of W automatic estimations with high temporal resolution. A new methodology, based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site, has been presented providing good results.
Jan Dousa, Pavel Vaclavovic, and Michal Elias
Atmos. Meas. Tech., 10, 3589–3607, https://doi.org/10.5194/amt-10-3589-2017, https://doi.org/10.5194/amt-10-3589-2017, 2017
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The second GOP reprocessing of EUREF network (1996 to 2014) produced GNSS tropospheric parameters for climate research. We performed and evaluated seven solutions and enhanced a strategy for the continuity of tropospheric parameters. Compared with Repro1, Repro2 yielded improvements of 50 % and 25 % in repeatability of horizontal and vertical coordinates and 9 % in tropospheric parameters. Tropospheric gradients revealed a strong sensitivity to GNSS tracking demonstrated at Mallorca station.
Fadwa Alshawaf, Kyriakos Balidakis, Galina Dick, Stefan Heise, and Jens Wickert
Atmos. Meas. Tech., 10, 3117–3132, https://doi.org/10.5194/amt-10-3117-2017, https://doi.org/10.5194/amt-10-3117-2017, 2017
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In this paper, we aimed at estimating climatic trends using precipitable water vapor time series and surface measurements of air temperature in Germany. We used GNSS, ERA-Interim, and synoptic data. The results show mainly a positive trend in precipitable water vapor and temperature with an increase in the trend when moving to northeastern Germany.
Leslie David, Olivier Bock, Christian Thom, Pierre Bosser, and Jacques Pelon
Atmos. Meas. Tech., 10, 2745–2758, https://doi.org/10.5194/amt-10-2745-2017, https://doi.org/10.5194/amt-10-2745-2017, 2017
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The Raman lidar ability to retrieve atmospheric water vapor with high accuracy makes it a premium instrument in different research fields such as climatology, meteorology, or calibration of GNSS altimetry data. In order to achieve long-term stability of the measurements, the system has to be carefully calibrated. In this work we strove to investigate and mitigate the error and instability sources through numerical simulations as well as experimental tests.
Alberto Caldas-Álvarez, Samiro Khodayar, and Olivier Bock
Adv. Sci. Res., 14, 157–162, https://doi.org/10.5194/asr-14-157-2017, https://doi.org/10.5194/asr-14-157-2017, 2017
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The representation of the atmospheric moisture distribution in weather and climate prediction models has been identified as a source of error in the representation of heavy precipitation events. This research work shows the relevance of overcoming deficiencies in the representation of the moisture content in the vertical direction, even after assimilating humidity data for a case study characteristic of the western Mediterranean by early autumn.
Michal Kačmařík, Jan Douša, Galina Dick, Florian Zus, Hugues Brenot, Gregor Möller, Eric Pottiaux, Jan Kapłon, Paweł Hordyniec, Pavel Václavovic, and Laurent Morel
Atmos. Meas. Tech., 10, 2183–2208, https://doi.org/10.5194/amt-10-2183-2017, https://doi.org/10.5194/amt-10-2183-2017, 2017
Rosa Pacione, Andrzej Araszkiewicz, Elmar Brockmann, and Jan Dousa
Atmos. Meas. Tech., 10, 1689–1705, https://doi.org/10.5194/amt-10-1689-2017, https://doi.org/10.5194/amt-10-1689-2017, 2017
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The use of ground-based GNSS data for climate research is an emerging field. The reprocessing activity under EUREF has been a huge effort, generating homogeneous tropospheric products to be used as a data set for monitoring trends in atmospheric water vapour. EPN-Repro2 data have been evaluated against RS and ERA-Interim data as well as in terms of ZTD trends. The obtained results show that they can be used for ZTD trend detection over Europe in areas where other data are not available.
Cuixian Lu, Florian Zus, Maorong Ge, Robert Heinkelmann, Galina Dick, Jens Wickert, and Harald Schuh
Atmos. Meas. Tech., 9, 5965–5973, https://doi.org/10.5194/amt-9-5965-2016, https://doi.org/10.5194/amt-9-5965-2016, 2016
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The recent dramatic development of multi-GNSS constellations brings great opportunities and potential for more enhanced precise positioning, navigation, timing, and other applications. In this contribution, we develop a numerical weather model (NWM) constrained PPP processing system to improve the multi-GNSS precise positioning. Compared to the standard PPP solution, significant improvements of both convergence time and positioning accuracy are achieved with the NWM-constrained PPP solution.
Siebren de Haan
Atmos. Meas. Tech., 9, 4141–4150, https://doi.org/10.5194/amt-9-4141-2016, https://doi.org/10.5194/amt-9-4141-2016, 2016
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The paper presents estimates of aircraft-derived wind observations obtained using Mode-S EHS method by applying the triple-collocation technique. Triple-collocated data sets were constructed using sodar (at Schiphol airport) and Doppler radar wind observation (from two radars in the Netherlands) in combination with numerical weather model data. It was found that the wind error near the surface is around 1.4 m s−1, while at 500 hPa the error is estimated to be around 1.1 m s−1.
Tzvetan Simeonov, Dmitry Sidorov, Felix Norman Teferle, Georgi Milev, and Guergana Guerova
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-152, https://doi.org/10.5194/amt-2016-152, 2016
Revised manuscript not accepted
Jan Douša, Galina Dick, Michal Kačmařík, Radmila Brožková, Florian Zus, Hugues Brenot, Anastasia Stoycheva, Gregor Möller, and Jan Kaplon
Atmos. Meas. Tech., 9, 2989–3008, https://doi.org/10.5194/amt-9-2989-2016, https://doi.org/10.5194/amt-9-2989-2016, 2016
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GNSS products provide observations of atmospheric water vapour. Advanced tropospheric products focus on ultra-fast and high-resolution zenith total delays (ZTDs), horizontal gradients and slant delays, all suitable for rapid-cycle numerical weather prediction (NWP) and severe weather event monitoring. The GNSS4SWEC Benchmark provides a complex data set for developing and assessing these products, with initial focus on reference ZTDs and gradients derived from several NWP and dense GNSS networks.
Jacek M. Kopeć, Kamil Kwiatkowski, Siebren de Haan, and Szymon P. Malinowski
Atmos. Meas. Tech., 9, 2253–2265, https://doi.org/10.5194/amt-9-2253-2016, https://doi.org/10.5194/amt-9-2253-2016, 2016
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This paper is presenting a feasibility study focused on methods of estimating the turbulence intensity based on a class of navigational messages routinely broadcast by the commercial aircraft (known as ADS-B and Mode-S). Using this kind of information could have potentially significant impact on aviation safety. Three methods have been investigated.
Fadwa Alshawaf, Galina Dick, Stefan Heise, Tzvetan Simeonov, Sibylle Vey, Torsten Schmidt, and Jens Wickert
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-151, https://doi.org/10.5194/amt-2016-151, 2016
Revised manuscript not accepted
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In this work, we use time series from GNSS, European Center for Medium-Range Weather Forecasts Reanalysis (ERA-Interim) data, and meteorological measurements to evaluate climate evolution in Central Europe. We monitor different atmospheric variables such as temperature, PWV, precipitation, and snow cover. The results show an increasing trend the water vapor time series that are correlated with the trend the temperature tme series. The average increase of water vapor is about 0.3–0.6 mm/decade .
T. Ning, J. Wang, G. Elgered, G. Dick, J. Wickert, M. Bradke, M. Sommer, R. Querel, and D. Smale
Atmos. Meas. Tech., 9, 79–92, https://doi.org/10.5194/amt-9-79-2016, https://doi.org/10.5194/amt-9-79-2016, 2016
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Integrated water vapour (IWV) obtained from GNSS is to be developed into a GRUAN data product. In addition to the actual measurement, this data product needs to provide an estimate of the measurement uncertainty at the same time resolution as the actual measurement. The method developed in the paper fulfils the requirement by assigning a specific uncertainty to each data point. The method is also valuable for all applications of GNSS IWV data in atmospheric research and weather forecast.
S. Steinke, S. Eikenberg, U. Löhnert, G. Dick, D. Klocke, P. Di Girolamo, and S. Crewell
Atmos. Chem. Phys., 15, 2675–2692, https://doi.org/10.5194/acp-15-2675-2015, https://doi.org/10.5194/acp-15-2675-2015, 2015
M. Shangguan, S. Heise, M. Bender, G. Dick, M. Ramatschi, and J. Wickert
Ann. Geophys., 33, 55–61, https://doi.org/10.5194/angeo-33-55-2015, https://doi.org/10.5194/angeo-33-55-2015, 2015
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We present validation results covering 184 days of SIWV (slant-integrated water vapor) observed by a ground-based GPS receiver and a WVR (water vapor radiometer). SIWV data from GPS and WVR generally show good agreement, and the relation between their differences and possible influential factors are analyzed. The differences in SIWV show a relative elevation dependence. Besides the elevation, dependencies between the atmospheric humidity conditions, temperature and differences in SIWV are found.
G. Guerova, T. Simeonov, and N. Yordanova
Atmos. Meas. Tech., 7, 2683–2694, https://doi.org/10.5194/amt-7-2683-2014, https://doi.org/10.5194/amt-7-2683-2014, 2014
R. Van Malderen, H. Brenot, E. Pottiaux, S. Beirle, C. Hermans, M. De Mazière, T. Wagner, H. De Backer, and C. Bruyninx
Atmos. Meas. Tech., 7, 2487–2512, https://doi.org/10.5194/amt-7-2487-2014, https://doi.org/10.5194/amt-7-2487-2014, 2014
O. Bock, P. Bosser, T. Bourcy, L. David, F. Goutail, C. Hoareau, P. Keckhut, D. Legain, A. Pazmino, J. Pelon, K. Pipis, G. Poujol, A. Sarkissian, C. Thom, G. Tournois, and D. Tzanos
Atmos. Meas. Tech., 6, 2777–2802, https://doi.org/10.5194/amt-6-2777-2013, https://doi.org/10.5194/amt-6-2777-2013, 2013
M. Shangguan, M. Bender, M. Ramatschi, G. Dick, J. Wickert, A. Raabe, and R. Galas
Ann. Geophys., 31, 1491–1505, https://doi.org/10.5194/angeo-31-1491-2013, https://doi.org/10.5194/angeo-31-1491-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Atmospheric propane (C3H8) column retrievals from ground-based FTIR observations in Xianghe, China
Can the remote sensing of combustion phase improve estimates of landscape fire smoke emission rate and composition?
Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS
Troposphere–stratosphere-integrated bromine monoxide (BrO) profile retrieval over the central Pacific Ocean
Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements
Merging TEMPEST microwave and GOES-16 geostationary IR soundings for improved water vapor profiles
Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission
Mapping the CO2 total column retrieval performance from shortwave infrared measurements: synthetic impacts of the spectral resolution, signal-to-noise ratio, and spectral band selection
Assessment of the contribution of the Meteosat Third Generation Infrared Sounder (MTG-IRS) for the characterisation of ozone over Europe
Assessing the potential of free-tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events
Current potential of CH4 emission estimates using TROPOMI in the Middle East
A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument
Estimation of biogenic volatile organic compound (BVOC) emissions in forest ecosystems using drone-based lidar, photogrammetry, and image recognition technologies
Fast retrieval of XCO2 over east Asia based on Orbiting Carbon Observatory-2 (OCO-2) spectral measurements
A new method for estimating megacity NOx emissions and lifetimes from satellite observations
Accounting for the effect of aerosols in GHGSat methane retrieval
NitroNet – A deep-learning NO2 profile retrieval prototype for the TROPOMI satellite instrument
A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B
Global retrieval of stratospheric and tropospheric BrO columns from the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on board the Suomi-NPP satellite
IMK–IAA MIPAS retrieval version 8: CH4 and N2O
Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak
U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates
Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera
The transition to new ozone absorption cross sections for Dobson and Brewer total ozone measurements
Advantages of assimilating multispectral satellite retrievals of atmospheric composition: a demonstration using MOPITT carbon monoxide products
An improved OMI ozone profile research product version 2.0 with collection 4 L1b data and algorithm updates
Tropospheric ozone column dataset from OMPS-LP/OMPS-NM limb–nadir matching
Version 8 IMK/IAA MIPAS measurements of CFC-11, CFC-12, and HCFC-22
The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product
Level0 to Level1B processor for MethaneAIR
Exploiting the entire near-infrared spectral range to improve the detection of methane plumes with high-resolution imaging spectrometers
The differences between remote sensing and in situ air pollutants measurements over the Canadian Oil Sands
Improved CCD tropospheric ozone from S5P TROPOMI satellite data using local cloud fields
A method for estimating localized CO2 emissions from co-located satellite XCO2 and NO2 images
The GeoCarb greenhouse gas retrieval algorithm: simulations and sensitivity to sources of uncertainty
Airborne lidar measurements of atmospheric CO2 column concentrations to cloud tops made during the 2017 ASCENDS/ABoVE campaign
Airborne observation with a low-cost hyperspectral instrument: retrieval of NO2 vertical column densities (VCDs) and the satellite sub-grid variability over industrial point sources
A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10
MIPAS ozone retrieval version 8: middle-atmosphere measurements
Atmospheric N2O and CH4 total columns retrieved from low-resolution Fourier transform infrared (FTIR) spectra (Bruker VERTEX 70) in the mid-infrared region
A new accurate retrieval algorithm of bromine monoxide columns inside minor volcanic plumes from Sentinel-5P TROPOMI observations
Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground
The IASI NH3 version 4 product: averaging kernels and improved consistency
A physically based correction for stray light in Brewer spectrophotometer data analysis
Optimal selection of satellite XCO2 images over cities for urban CO2 emission monitoring using a global adaptive-mesh model
A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm
Methane retrievals from airborne HySpex observations in the shortwave infrared
Feasibility analysis of optimal terahertz (THz) bands for passive limb sounding of middle and upper atmospheric wind
Minqiang Zhou, Pucai Wang, Bart Dils, Bavo Langerock, Geoff Toon, Christian Hermans, Weidong Nan, Qun Cheng, and Martine De Mazière
Atmos. Meas. Tech., 17, 6385–6396, https://doi.org/10.5194/amt-17-6385-2024, https://doi.org/10.5194/amt-17-6385-2024, 2024
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Solar absorption spectra near 2967 cm−1 recorded by a ground-based FTIR with a high spectral resolution of 0.0035 cm-1 are applied to retrieve C3H8 columns for the first time in Xianghe, China, within the NDACC-IRWG. The mean and standard deviation of the C3H8 columns are 1.80 ± 0.81 (1σ) × 1015 molec. cm-2. Good correlations are found between C3H8 and other non-methane hydrocarbons, such as C2H6 (R = 0.84) and C2H2 (R = 0.79), as well as between C3H8 and CO (R = 0.72).
Farrer Owsley-Brown, Martin J. Wooster, Mark J. Grosvenor, and Yanan Liu
Atmos. Meas. Tech., 17, 6247–6264, https://doi.org/10.5194/amt-17-6247-2024, https://doi.org/10.5194/amt-17-6247-2024, 2024
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Landscape fires produce vast amounts of smoke, affecting the atmosphere locally and globally. Whether a fire is flaming or smouldering strongly impacts the rate at which smoke is produced as well as its composition. This study tested two methods to determine these combustion phases in laboratory fires and compared them to the smoke emitted. One of these methods improved estimates of smoke emission significantly. This suggests potential for improvement in global emission estimates.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024, https://doi.org/10.5194/amt-17-6163-2024, 2024
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In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.
Theodore K. Koenig, François Hendrick, Douglas Kinnison, Christopher F. Lee, Michel Van Roozendael, and Rainer Volkamer
Atmos. Meas. Tech., 17, 5911–5934, https://doi.org/10.5194/amt-17-5911-2024, https://doi.org/10.5194/amt-17-5911-2024, 2024
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Atmospheric bromine destroys ozone, impacts oxidation capacity, and oxidizes mercury into its toxic form. We constrain bromine by remote sensing of BrO from a mountaintop. Previous measurements retrieved two to three pieces of information vertically; we apply new methods to get five and a half vertically and two more in time. We compare with aircraft measurements to validate the methods and look at variations in BrO over the Pacific.
Kavitha Mottungan, Chayan Roychoudhury, Vanessa Brocchi, Benjamin Gaubert, Wenfu Tang, Mohammad Amin Mirrezaei, John McKinnon, Yafang Guo, David W. T. Griffith, Dietrich G. Feist, Isamu Morino, Mahesh K. Sha, Manvendra K. Dubey, Martine De Mazière, Nicholas M. Deutscher, Paul O. Wennberg, Ralf Sussmann, Rigel Kivi, Tae-Young Goo, Voltaire A. Velazco, Wei Wang, and Avelino F. Arellano Jr.
Atmos. Meas. Tech., 17, 5861–5885, https://doi.org/10.5194/amt-17-5861-2024, https://doi.org/10.5194/amt-17-5861-2024, 2024
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A combination of data analysis techniques is introduced to separate local and regional influences on observed levels of carbon dioxide, carbon monoxide, and methane from an established ground-based remote sensing network. We take advantage of the covariations in these trace gases to identify the dominant type of sources driving these levels. Applying these methods in conjunction with existing approaches to other datasets can better address uncertainties in identifying sources and sinks.
Chia-Pang Kuo and Christian Kummerow
Atmos. Meas. Tech., 17, 5637–5653, https://doi.org/10.5194/amt-17-5637-2024, https://doi.org/10.5194/amt-17-5637-2024, 2024
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A small satellite about the size of a shoe box, named TEMPEST, carries only a microwave sensor and is designed to measure the water cycle of the Earth from space in an economical way compared with traditional satellites, which have additional infrared sensors. To overcome the limitation, extra infrared signals from GOES-R ABI are combined with TEMPEST microwave measurements. Compared with ground observations, improved humidity information is extracted from the merged TEMPEST and ABI signals.
Christopher Chan Miller, Sébastien Roche, Jonas S. Wilzewski, Xiong Liu, Kelly Chance, Amir H. Souri, Eamon Conway, Bingkun Luo, Jenna Samra, Jacob Hawthorne, Kang Sun, Carly Staebell, Apisada Chulakadabba, Maryann Sargent, Joshua S. Benmergui, Jonathan E. Franklin, Bruce C. Daube, Yang Li, Joshua L. Laughner, Bianca C. Baier, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, https://doi.org/10.5194/amt-17-5429-2024, 2024
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MethaneSAT is an upcoming satellite mission designed to monitor methane emissions from the oil and gas (O&G) industry globally. Here, we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted on an aircraft. MethaneAIR can map methane with high precision and accuracy over a typically sized oil and gas basin (~200 km2) in a single flight. This paper demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Matthieu Dogniaux and Cyril Crevoisier
Atmos. Meas. Tech., 17, 5373–5396, https://doi.org/10.5194/amt-17-5373-2024, https://doi.org/10.5194/amt-17-5373-2024, 2024
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Many CO2-observing satellite concepts, with very different design choices and trade-offs, are expected to be put into orbit during the upcoming decade. This work uses numerical simulations to explore the impact of critical design parameters on the performance of upcoming CO2-observing satellite concepts.
Francesca Vittorioso, Vincent Guidard, and Nadia Fourrié
Atmos. Meas. Tech., 17, 5279–5299, https://doi.org/10.5194/amt-17-5279-2024, https://doi.org/10.5194/amt-17-5279-2024, 2024
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The future Meteosat Third Generation Infrared Sounder (MTG-IRS) will represent a major innovation for the monitoring of the chemical state of the atmosphere. MTG-IRS will have the advantage of being based on a geostationary platform and acquiring data with a high temporal frequency. This work aims to evaluate its potential impact over Europe within a chemical transport model (MOCAGE). The results indicate that the assimilation of these data always has a positive impact on ozone analysis.
Matthias Schneider, Kinya Toride, Farahnaz Khosrawi, Frank Hase, Benjamin Ertl, Christopher J. Diekmann, and Kei Yoshimura
Atmos. Meas. Tech., 17, 5243–5259, https://doi.org/10.5194/amt-17-5243-2024, https://doi.org/10.5194/amt-17-5243-2024, 2024
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Despite its importance for extreme weather and climate feedbacks, atmospheric convection is not well constrained. This study assesses the potential of novel tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events. We find that the impact of the isotopologues is small for stable atmospheric conditions but significant for unstable conditions, which have the strongest societal impacts (e.g. storms and flooding).
Mengyao Liu, Ronald van der A, Michiel van Weele, Lotte Bryan, Henk Eskes, Pepijn Veefkind, Yongxue Liu, Xiaojuan Lin, Jos de Laat, and Jieying Ding
Atmos. Meas. Tech., 17, 5261–5277, https://doi.org/10.5194/amt-17-5261-2024, https://doi.org/10.5194/amt-17-5261-2024, 2024
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A new divergence method was developed and applied to estimate methane emissions from TROPOMI observations over the Middle East, where it is typically challenging for a satellite to measure methane due to its complicated orography and surface albedo. Our results show the potential of TROPOMI to quantify methane emissions from various sources rather than big emitters from space after objectively excluding the artifacts in the retrieval.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Xianzhong Duan, Ming Chang, Guotong Wu, Suping Situ, Shengjie Zhu, Qi Zhang, Yibo Huangfu, Weiwen Wang, Weihua Chen, Bin Yuan, and Xuemei Wang
Atmos. Meas. Tech., 17, 4065–4079, https://doi.org/10.5194/amt-17-4065-2024, https://doi.org/10.5194/amt-17-4065-2024, 2024
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Accurately estimating biogenic volatile organic compound (BVOC) emissions in forest ecosystems has been challenging. This research presents a framework that utilizes drone-based lidar, photogrammetry, and image recognition technologies to identify plant species and estimate BVOC emissions. The largest cumulative isoprene emissions were found in the Myrtaceae family, while those of monoterpenes were from the Rubiaceae family.
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech., 17, 3949–3967, https://doi.org/10.5194/amt-17-3949-2024, https://doi.org/10.5194/amt-17-3949-2024, 2024
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This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than using traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Steffen Beirle and Thomas Wagner
Atmos. Meas. Tech., 17, 3439–3453, https://doi.org/10.5194/amt-17-3439-2024, https://doi.org/10.5194/amt-17-3439-2024, 2024
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We present a new method for estimating emissions and lifetimes for nitrogen oxides emitted from large cities by using satellite NO2 observations combined with wind fields. The estimate is based on the simultaneous evaluation of the downwind plumes for opposing wind directions. This allows us to derive seasonal mean emissions and lifetimes for 100 cities around the globe.
Qiurun Yu, Dylan Jervis, and Yi Huang
Atmos. Meas. Tech., 17, 3347–3366, https://doi.org/10.5194/amt-17-3347-2024, https://doi.org/10.5194/amt-17-3347-2024, 2024
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This study estimated the effects of aerosols on GHGSat satellite methane retrieval and investigated the performance of simultaneously retrieving aerosol and methane information using a multi-angle viewing method. Results suggested that the performance of GHGSat methane retrieval improved when aerosols were considered, and the multi-angle viewing method is insensitive to the satellite angle setting. This performance assessment is useful for improving future GHGSat-like instruments.
Leon Kuhn, Steffen Beirle, Sergey Osipov, Andrea Pozzer, and Thomas Wagner
EGUsphere, https://doi.org/10.5194/egusphere-2024-1196, https://doi.org/10.5194/egusphere-2024-1196, 2024
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This paper presents a new machine-learning model, which allows to compute NO2 concentration profiles from satellite observations. The neural network was trained on synthetic data from the regional chemistry and transport model WRF-Chem. It is the first model of this kind. We present a thorough model validation study, including different seasons and regions of the world.
Zhonghua He, Ling Gao, Miao Liang, and Zhao-Cheng Zeng
Atmos. Meas. Tech., 17, 2937–2956, https://doi.org/10.5194/amt-17-2937-2024, https://doi.org/10.5194/amt-17-2937-2024, 2024
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Using Gaofen-5B satellite data, this study detected 93 methane plume events from 32 coal mines in Shanxi, China, with emission rates spanning from 761.78 ± 185.00 to 12729.12 ± 4658.13 kg h-1, showing significant variability among sources. This study highlights Gaofen-5B’s capacity for monitoring large methane point sources, offering valuable support in reducing greenhouse gas emissions.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
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We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 17, 2849–2871, https://doi.org/10.5194/amt-17-2849-2024, https://doi.org/10.5194/amt-17-2849-2024, 2024
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We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument on board the Environmental Satellite (Envisat) during 2002 to 2012. Monitoring of these gases is of scientific interest because both of them are strong greenhouse gases. We analyze the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
Atmos. Meas. Tech., 17, 2777–2787, https://doi.org/10.5194/amt-17-2777-2024, https://doi.org/10.5194/amt-17-2777-2024, 2024
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We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 502 ± 464 t h−1.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
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Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 2583–2593, https://doi.org/10.5194/amt-17-2583-2024, https://doi.org/10.5194/amt-17-2583-2024, 2024
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Methane is a potent greenhouse gas that has been responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions comprise an important step in combating the climate crisis. We develop a new deep learning model to automatically detect methane plumes from satellite images and demonstrate that this can be applied to monitor large methane emissions resulting from the oil and gas industry.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 17, 2317–2334, https://doi.org/10.5194/amt-17-2317-2024, https://doi.org/10.5194/amt-17-2317-2024, 2024
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FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and André Butz
Atmos. Meas. Tech., 17, 2257–2275, https://doi.org/10.5194/amt-17-2257-2024, https://doi.org/10.5194/amt-17-2257-2024, 2024
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Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Karl Voglmeier, Voltaire A. Velazco, Luca Egli, Julian Gröbner, Alberto Redondas, and Wolfgang Steinbrecht
Atmos. Meas. Tech., 17, 2277–2294, https://doi.org/10.5194/amt-17-2277-2024, https://doi.org/10.5194/amt-17-2277-2024, 2024
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Comparison between total ozone column (TOC) measurements from ground-based Dobson and Brewer spectrophotometers generally reveals seasonally varying differences of a few percent. This study recommends a new TOC retrieval approach, which effectively eliminates these seasonally varying differences by applying new ozone absorption cross sections, appropriate slit functions for the Dobson instrument, and climatological values for the effective ozone temperature.
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, and Helen Worden
Atmos. Meas. Tech., 17, 1941–1963, https://doi.org/10.5194/amt-17-1941-2024, https://doi.org/10.5194/amt-17-1941-2024, 2024
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We assimilate different MOPITT CO products to understand the impact of (1) assimilating multispectral and joint retrievals versus single spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral and joint retrievals versus assimilating individual products separately.
Juseon Bak, Xiong Liu, Kai Yang, Gonzalo Gonzalez Abad, Ewan O'Sullivan, Kelly Chance, and Cheol-Hee Kim
Atmos. Meas. Tech., 17, 1891–1911, https://doi.org/10.5194/amt-17-1891-2024, https://doi.org/10.5194/amt-17-1891-2024, 2024
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The new version (V2) of the OMI ozone profile product is introduced to improve retrieval quality and long-term consistency of tropospheric ozone by incorporating the recent collection 4 OMI L1b spectral products and refining radiometric correction, forward model calculation, and a priori ozone data.
Andrea Orfanoz-Cheuquelaf, Carlo Arosio, Alexei Rozanov, Mark Weber, Annette Ladstätter-Weißenmayer, John P. Burrows, Anne M. Thompson, Ryan M. Stauffer, and Debra E. Kollonige
Atmos. Meas. Tech., 17, 1791–1809, https://doi.org/10.5194/amt-17-1791-2024, https://doi.org/10.5194/amt-17-1791-2024, 2024
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Valuable information on the tropospheric ozone column (TrOC) can be obtained globally by combining space-borne limb and nadir measurements (limb–nadir matching, LNM). This study describes the retrieval of TrOC from the OMPS instrument (since 2012) using the LNM technique. The OMPS-LNM TrOC was compared with ozonesondes and other satellite measurements, showing a good agreement with a negative bias within 1 to 4 DU. This new dataset is suitable for pollution studies.
Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Bernd Funke, Maya García-Comas, and Manuel López-Puertas
Atmos. Meas. Tech., 17, 1759–1789, https://doi.org/10.5194/amt-17-1759-2024, https://doi.org/10.5194/amt-17-1759-2024, 2024
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CFC-11, CFC-12, and HCFC-22 contribute to the depletion of ozone and are potent greenhouse gases. They have been banned by the Montreal protocol. With MIPAS on Envisat the atmospheric composition could be observed between 2002 and 2012. We present here the retrieval of their atmospheric distributions for the final data version 8. We characterise the derived data by their error budget and their spatial resolution. An additional representation for direct comparison to models is also provided.
Nicole Jacobs, Christopher W. O'Dell, Thomas E. Taylor, Thomas L. Logan, Brendan Byrne, Matthäus Kiel, Rigel Kivi, Pauli Heikkinen, Aronne Merrelli, Vivienne H. Payne, and Abhishek Chatterjee
Atmos. Meas. Tech., 17, 1375–1401, https://doi.org/10.5194/amt-17-1375-2024, https://doi.org/10.5194/amt-17-1375-2024, 2024
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The accuracy of trace gas retrievals from spaceborne observations, like those from the Orbiting Carbon Observatory 2 (OCO-2), are sensitive to the referenced digital elevation model (DEM). Therefore, we evaluate several global DEMs, used in versions 10 and 11 of the OCO-2 retrieval along with the Copernicus DEM. We explore the impacts of changing the DEM on biases in OCO-2-retrieved XCO2 and inferred CO2 fluxes. Our findings led to an update to OCO-2 v11.1 using the Copernicus DEM globally.
Eamon K. Conway, Amir H. Souri, Joshua Benmergui, Kang Sun, Xiong Liu, Carly Staebell, Christopher Chan Miller, Jonathan Franklin, Jenna Samra, Jonas Wilzewski, Sebastien Roche, Bingkun Luo, Apisada Chulakadabba, Maryann Sargent, Jacob Hohl, Bruce Daube, Iouli Gordon, Kelly Chance, and Steven Wofsy
Atmos. Meas. Tech., 17, 1347–1362, https://doi.org/10.5194/amt-17-1347-2024, https://doi.org/10.5194/amt-17-1347-2024, 2024
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The work presented here describes the processes required to convert raw sensor data for the MethaneAIR instrument to geometrically calibrated data. Each algorithm is described in detail. MethaneAIR is the airborne simulator for MethaneSAT, a new satellite under development by MethaneSAT LLC, a subsidiary of the EDF. MethaneSAT's goals are to precisely map over 80 % of the production sources of methane emissions from oil and gas fields across the globe to a high degree of accuracy.
Javier Roger, Luis Guanter, Javier Gorroño, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 1333–1346, https://doi.org/10.5194/amt-17-1333-2024, https://doi.org/10.5194/amt-17-1333-2024, 2024
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Methane emissions can be identified using remote sensing, but surface-related structures disturb detection. In this work, a variation of the matched filter method that exploits a large fraction of the near-infrared range (1000–2500 nm) is applied. In comparison to the raw matched filter, it reduces background noise and strongly attenuates the surface-related artifacts, which leads to a greater detection capability. We propose this variation as a standard methodology for methane detection.
Xiaoyi Zhao, Vitali Fioletov, Debora Griffin, Chris McLinden, Ralf Staebler, Cristian Mihele, Kevin Strawbridge, Jonathan Davies, Ihab Abboud, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, and Robert Swap
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-27, https://doi.org/10.5194/amt-2024-27, 2024
Revised manuscript accepted for AMT
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This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing, and in situ observations in air quality monitoring. It shows the meteorological conditions (wind directions, speed, and boundary layer conditions) will strongly affect the agreement between the two measurements.
Swathi Maratt Satheesan, Kai-Uwe Eichmann, John P. Burrows, Mark Weber, Ryan Stauffer, Anne M. Thompson, and Debra Kollonige
EGUsphere, https://doi.org/10.5194/egusphere-2023-2825, https://doi.org/10.5194/egusphere-2023-2825, 2024
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CHORA, an advanced CCD technique, enhances the accuracy of tropospheric ozone retrievals. Unlike the traditional Pacific cloud reference sector (CPC) scheme, CHORA introduces a local cloud reference sector (CLC ) and an alternative approach (CLCT) for precision. Analysing monthly averaged TROPOMI data from 2018 to 2022 and validating with SHADOZ ozonesonde data, CLCT outperforms other methods, emerging as the preferred choice, especially in future geostationary satellite missions.
Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows
Atmos. Meas. Tech., 17, 1145–1173, https://doi.org/10.5194/amt-17-1145-2024, https://doi.org/10.5194/amt-17-1145-2024, 2024
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We developed a method to estimate CO2 emissions from localized sources, such as power plants, using satellite data and applied it to estimate CO2 emissions from the Bełchatów Power Station (Poland). As the detection of CO2 emission plumes from satellite data is difficult, we used observations of co-emitted NO2 to constrain the emission plume region. Our results agree with CO2 emission estimations based on the power-plant-generated power and emission factors.
Gregory R. McGarragh, Christopher W. O'Dell, Sean M. R. Crowell, Peter Somkuti, Eric B. Burgh, and Berrien Moore III
Atmos. Meas. Tech., 17, 1091–1121, https://doi.org/10.5194/amt-17-1091-2024, https://doi.org/10.5194/amt-17-1091-2024, 2024
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Carbon dioxide and methane are greenhouse gases that have been rapidly increasing due to human activity since the industrial revolution, leading to global warming and subsequently negative affects on the climate. It is important to measure the concentrations of these gases in order to make climate predictions that drive policy changes to mitigate climate change. GeoCarb aims to measure the concentrations of these gases from space over the Americas at unprecedented spatial and temporal scales.
Jianping Mao, James B. Abshire, S. Randy Kawa, Xiaoli Sun, and Haris Riris
Atmos. Meas. Tech., 17, 1061–1074, https://doi.org/10.5194/amt-17-1061-2024, https://doi.org/10.5194/amt-17-1061-2024, 2024
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NASA Goddard Space Flight Center has developed an integrated-path, differential absorption lidar approach to measure column-averaged atmospheric CO2 (XCO2). We demonstrated the lidar’s capability to measure XCO2 to cloud tops ,as well as to the ground, with the data from the summer 2017 airborne campaign in the US and Canada. This active remote sensing technique can provide all-sky data coverage and high-quality XCO2 measurements for future airborne science campaigns and space missions.
Jong-Uk Park, Hyun-Jae Kim, Jin-Soo Park, Jinsoo Choi, Sang Seo Park, Kangho Bae, Jong-Jae Lee, Chang-Keun Song, Soojin Park, Kyuseok Shim, Yeonsoo Cho, and Sang-Woo Kim
Atmos. Meas. Tech., 17, 197–217, https://doi.org/10.5194/amt-17-197-2024, https://doi.org/10.5194/amt-17-197-2024, 2024
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The high-spatial-resolution NO2 vertical column densities (VCDs) were measured from airborne observations using the low-cost hyperspectral imaging sensor (HIS) at three industrial areas in South Korea with the newly developed versatile NO2 VCD retrieval algorithm apt to be applied to the instruments with volatile optical and radiometric properties. The airborne HIS observations emphasized the intensifying satellite sub-grid variability in NO2 VCDs near the emission sources.
William R. Keely, Steffen Mauceri, Sean Crowell, and Christopher W. O'Dell
Atmos. Meas. Tech., 16, 5725–5748, https://doi.org/10.5194/amt-16-5725-2023, https://doi.org/10.5194/amt-16-5725-2023, 2023
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Measurement errors in satellite observations of CO2 attributed to co-estimated atmospheric variables are corrected using a linear regression on quality-filtered data. We propose a nonlinear method that improves correction against a set of ground truth proxies and allows for high throughput of well-corrected data.
Manuel López-Puertas, Maya García-Comas, Bernd Funke, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 5609–5645, https://doi.org/10.5194/amt-16-5609-2023, https://doi.org/10.5194/amt-16-5609-2023, 2023
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This paper describes a new version (V8) of ozone data from MIPAS middle-atmosphere spectra. The dataset comprises high-quality ozone profiles from 20 to 100 km, with pole-to-pole latitude coverage for the day- and nighttime, spanning 2005 until 2012. An exhaustive treatment of errors has been performed. Compared to other satellite instruments, MIPAS ozone shows a positive bias of 5 %–8 % below 70 km. In the upper mesosphere, this new version agrees much better than previous ones (within 10 %).
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Christian Hermans, Nicolas Kumps, Rigel Kivi, Pauli Heikkinen, Christof Petri, Justus Notholt, Huilin Chen, and Martine De Mazière
Atmos. Meas. Tech., 16, 5593–5608, https://doi.org/10.5194/amt-16-5593-2023, https://doi.org/10.5194/amt-16-5593-2023, 2023
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Atmospheric N2O and CH4 columns are successfully retrieved from low-resolution FTIR spectra recorded by a Bruker VERTEX 70. The 1-year measurements at Sodankylä show that the N2O total columns retrieved from 125HR and VERTEX 70 spectra are −0.3 ± 0.7 % with an R value of 0.93. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX spectra are 0.0 ± 0.8 % with an R value of 0.87. Such a technique can help to fill the gap in NDACC N2O and CH4 measurements.
Simon Warnach, Holger Sihler, Christian Borger, Nicole Bobrowski, Steffen Beirle, Ulrich Platt, and Thomas Wagner
Atmos. Meas. Tech., 16, 5537–5573, https://doi.org/10.5194/amt-16-5537-2023, https://doi.org/10.5194/amt-16-5537-2023, 2023
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BrO inside volcanic gas plumes but can be used in combination with SO2 to characterize the volcanic property and its activity state. High-quality satellite observations can provide a global inventory of this important quantity. This paper investigates how to accurately detect BrO inside volcanic plumes from the satellite UV spectrum. A sophisticated novel non-volcanic background correction scheme is presented, and systematic errors including cross-interference with formaldehyde are minimized.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
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Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Lieven Clarisse, Bruno Franco, Martin Van Damme, Tommaso Di Gioacchino, Juliette Hadji-Lazaro, Simon Whitburn, Lara Noppen, Daniel Hurtmans, Cathy Clerbaux, and Pierre Coheur
Atmos. Meas. Tech., 16, 5009–5028, https://doi.org/10.5194/amt-16-5009-2023, https://doi.org/10.5194/amt-16-5009-2023, 2023
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Ammonia is an important atmospheric pollutant. This article presents version 4 of the algorithm which retrieves ammonia abundances from the infrared measurements of the satellite sounder IASI. A measurement operator is introduced that can emulate the measurements (so-called averaging kernels) and measurement uncertainty is better characterized. Several other changes to the product itself are also documented, most of which improve the temporal consistency of the 2007–2022 IASI NH3 dataset.
Vladimir Savastiouk, Henri Diémoz, and C. Thomas McElroy
Atmos. Meas. Tech., 16, 4785–4806, https://doi.org/10.5194/amt-16-4785-2023, https://doi.org/10.5194/amt-16-4785-2023, 2023
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This paper describes a way to significantly improve ozone measurements at low sun elevations and large ozone amounts when using the Brewer ozone spectrophotometer. The proposed algorithm will allow more uniform ozone measurements across the monitoring network. This will contribute to more reliable trend analysis and support the satellite validation. This research contributes to better understanding the physics of the instrument, and the new algorithm is based on this new knowledge.
Alexandre Danjou, Grégoire Broquet, Andrew Schuh, François-Marie Bréon, and Thomas Lauvaux
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-199, https://doi.org/10.5194/amt-2023-199, 2023
Preprint under review for AMT
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We study the capacity of XCO2 space-borne imagery to estimate urban CO2 emissions with synthetic data. We define automatic and standard methods, and objective criteria for image selection. Wind variability and urban emission budget guide the emission estimation error. Images with low wind variability and high urban emissions account for 47 % of images and give a bias on the emission estimation of -7 % of the emissions and a spread of 56 %. Other images give a bias of -31 % and a spread of 99 %.
Yuhang Zhang, Jintai Lin, Jhoon Kim, Hanlim Lee, Junsung Park, Hyunkee Hong, Michel Van Roozendael, Francois Hendrick, Ting Wang, Pucai Wang, Qin He, Kai Qin, Yongjoo Choi, Yugo Kanaya, Jin Xu, Pinhua Xie, Xin Tian, Sanbao Zhang, Shanshan Wang, Siyang Cheng, Xinghong Cheng, Jianzhong Ma, Thomas Wagner, Robert Spurr, Lulu Chen, Hao Kong, and Mengyao Liu
Atmos. Meas. Tech., 16, 4643–4665, https://doi.org/10.5194/amt-16-4643-2023, https://doi.org/10.5194/amt-16-4643-2023, 2023
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Our tropospheric NO2 vertical column density product with high spatiotemporal resolution is based on the Geostationary Environment Monitoring Spectrometer (GEMS) and named POMINO–GEMS. Strong hotspot signals and NO2 diurnal variations are clearly seen. Validations with multiple satellite products and ground-based, mobile car and surface measurements exhibit the overall great performance of the POMINO–GEMS product, indicating its capability for application in environmental studies.
Philipp Hochstaffl, Franz Schreier, Claas Henning Köhler, Andreas Baumgartner, and Daniele Cerra
Atmos. Meas. Tech., 16, 4195–4214, https://doi.org/10.5194/amt-16-4195-2023, https://doi.org/10.5194/amt-16-4195-2023, 2023
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The study examines methane enhancements inferred from hyperspectral imaging observations using different retrieval schemes. One of the core challenges is the high spatial and moderate spectral resolution as it makes separation of spectral variations caused by molecular absorption and surface reflectivity challenging. It was found that localized methane enhancements can be detected and quantified from HySpex airborne observations using various retrieval schemes.
Wenyu Wang, Jian Xu, and Zhenzhan Wang
Atmos. Meas. Tech., 16, 4137–4153, https://doi.org/10.5194/amt-16-4137-2023, https://doi.org/10.5194/amt-16-4137-2023, 2023
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This article presents a study for feasibility analysis of atmospheric wind measurement using a terahertz (THz) passive limb radiometer with high spectral resolution. The simulations show that line-of-sight wind from 40 to 120 km can be obtained better than 10 m s−1 (at most altitudes it is better than 5 m s−1) using the O3, O2, H2O, and OI bands. This study will provide reference for future payload design.
Cited articles
Allen, M. R. and Ingram, W. J.: Constraints on future changes in climate and the hydrologic cycle, Nature, 419, 224–232, https://doi.org/10.1038/nature01092, 2002.
Arriola, J. S., Lindskog, M., Thorsteinsson, S., and Bojarova, J.: Variational Bias Correction of GNSS ZTD in the HARMONIE Modeling System, J. App. Meteorol. Clim., 55, 1259–1276, https://doi.org/10.1175/JAMC-D-15-0137.1, 2016.
Baelen, J. V., Reverdy, M., Tridon, F., Labbouz, L., Dick, G., Bender, M., and Hagen, M.: On the relationship between water vapour field evolution and the life cycle of precipitation systems, Q. J. Roy. Meteor. Soc., 137, 204–223, https://doi.org/10.1002/qj.785, 2011.
Bar-Sever, Y.: Reprocessed IGS Trop Product now available with Gradients, IGSMAIL-6298, available at: http://igscb.jpl.nasa.gov/pipermail/igsmail/2010/007488.html, 2012.
Bauer, H.-S., Wulfmeyer, V., Schwitalla, T., Zus, F., and Grzeschik, M.: Operational assimilation of GPS slant path delay measurements into the MM5 4DVAR system, Tellus A, 63, 263–282, https://doi.org/10.1111/j.1600-0870.2010.00489.x, 2011.
Behrend, D., Haas, R., D. Pino, L. P. G., Keihm, S. J., Schwarz, W., Cucurull, L., and Rius, A.: MM5 derived ZWDs compared to observational results from VLBI, GPS and WVR, Phys. Chem. Earth Pt. A, 27, 301–308, https://doi.org/10.1016/S1474-7065(02)00004-9, 2002.
Bender, M., Dick, G., Ge, M., Deng, Z., Wickert, J., Kahle, H.-G., Raabe, A., and Tetzlaff, G.: Development of a GNSS Water Vapor Tomography System Using Algebraic Reconstruction Techniques, Adv. Space Res., 47, 1704–1720, https://doi.org/10.1016/j.asr.2010.05.034, 2011a.
Bender, M., Stosius, R., Zus, F., Dick, G., Wickert, J., and Raabe, A.: GNSS water vapour tomography – Expected improvements by combining GPS, GLONASS and Galileo observations, Adv. Space Res., 47, 886–897, https://doi.org/10.1016/j.asr.2010.09.011, 2011b.
Benevides, P., Catalao, J., and Miranda, P. M.: Experimental GNSS tomography study in Lisbon (Portugal), Fisica de la Tierra, 26, 65–79, https://revistas.ucm.es/index.php/FITE/article/view/46972, 2014.
Bengtsson, L.: The global atmospheric water cycle, Environ. Res. Lett., 5, 025202, https://doi.org/10.1088/1748-9326/5/2/025202, 2010.
Bennitt, G. V. and Jupp, A.: Operational Assimilation of GPS Zenith Total Delay Observations into the Met Office Numerical Weather Prediction Models, Mon. Weather Rev., 140, 2706–2719, https://doi.org/10.1175/MWR-D-11-00156.1, 2012.
Bevis, M., Businger, S., Herring, T. A., Rocken, C., Anthes, R. A., and Ware, R. H.: GPS Meteorology: Remote Sensing of Atmospheric Water Vapour Using the Global Positioning System, J. Geophys. Res., 97, 15787–15801, https://doi.org/10.1029/92JD01517, 1992.
Bevis, M., Businger, S., Chiswell, S., Herring, T. A., Anthes, R. A., Rocken, C., and Ware, R. H.: GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water, J. App. Meteorol., 33, 379–386, https://doi.org/10.1175/1520-0450(1994)033<0379:GMMZWD>2.0.CO;2, 1994.
Bock, O., Keil, C., Richard, E., Flamant, C., and Bouin, M.-N.: Validation of precipitable water from ECMWF model analyses with GPS and radiosonde data during the MAP SOP, Q. J. Roy. Meteorol. Soc., 131, 3013–3036, https://doi.org/10.1256/qj.05.27, 2005.
Bock, O., Bouin, M. N., Walpersdorf, A., Lafore, J. P., Janicot, S., Guichard, F., and Agusti-Panareda, A.: Comparison of ground-based GPS precipitable water vapour to independent observations and NWP model reanalyses over Africa, Q. J. Roy. Meteor. Soc., 133, 2011–2027, https://doi.org/10.1002/qj.185, 2007.
Bock, O., Willis, P., Lacarra, M., and Bosser, P.: An inter-comparison of zenith tropospheric delays derived from DORIS and GPS data, Adv. Space Res., 46, 1648–1660, https://doi.org/10.1016/j.asr.2010.05.018, 2010.
Bock, O., Willis, P., Wang, J., and Mears, C.: A high-quality, homogenized, global, long-term (1993–2008) DORIS precipitable water data set for climate monitoring and model verification, J. Geophys. Res., 119, 7209–7230, https://doi.org/10.1002/2013JD021124, 2014.
Böhm, J. and Schuh, S.: Vienna Mapping Function in VLBI Analysis, Geophys. Res. Lett., 31, L01603, https://doi.org/10.1029/2003GL018984, 2004.
Böhm, J. and Schuh, S.: Troposheric gradients from the ECMWF in VLBI analysis, J. Geod., 81, 403–408, https://doi.org/10.1007/s00190-007-0144-2, 2007.
Braun, J., Rocken, C., Meertens, C., and Ware, R.: Development of a Water Vapor Tomography System Using Low Cost L1 GPS Receivers, 9th ARM Science Team Meeting Proceedings, San Antonio, Texas, 22–26 March, 1999.
Brenot, H., Ducrocq, V., Walpersdorf, A., Champollion, C., and Caumont, O.: GPS zenith delay sensitivity evaluated from high-resolution numerical weather prediction simulations of the 8–9 September 2002 flash flood over southeastern France, J. Geophys. Res., 111, D15105, https://doi.org/10.1029/2004JD005726, 2006.
Brenot, H., Neméghaire, J., Delobbe, L., Clerbaux, N., De Meutter, P., Deckmyn, A., Delcloo, A., Frappez, L., and Van Roozendael, M.: Preliminary signs of the initiation of deep convection by GNSS, Atmos. Chem. Phys., 13, 5425–5449, https://doi.org/10.5194/acp-13-5425-2013, 2013.
Brenot, H., Walpersdorf, A., Reverdy, M., van Baelen, J., Ducrocq, V., Champollion, C., Masson, F., Doerflinger, E., Collard, P., and Giroux, P.: A GPS network for tropospheric tomography in the framework of the Mediterranean hydrometeorological observatory Cévennes-Vivarais (southeastern France), Atmos. Meas. Tech., 7, 553–578, https://doi.org/10.5194/amt-7-553-2014, 2014.
Buehler, S. A., Östman, S., Melsheimer, C., Holl, G., Eliasson, S., John, V. O., Blumenstock, T., Hase, F., Elgered, G., Raffalski, U., Nasuno, T., Satoh, M., Milz, M., and Mendrok, J.: A multi-instrument comparison of integrated water vapour measurements at a high latitude site, Atmos. Chem. Phys., 12, 10925–10943, https://doi.org/10.5194/acp-12-10925-2012, 2012.
Byram, S. and Hackman, C.: Computation of the IGS Final Troposphere Product by the USNO, IGS workshop poster presentation, 2012.
Byun, S. and Bar-Sever, Y.: A new type of troposphere zenith path delay product of the international GNSS service, J. Geod., 83, 367–373, https://doi.org/10.1007/s00190-008-0288-8, 2009.
Caissy, M., Agrotis, L., Weber, G., Hernandez-Pajares, M., and Hugentobler, U.: INNOVATION-Coming Soon-The International GNSS Real-Time Service, GPS World, 23, 52–58, 2012.
Champollion, C., Flamant, C., Bock, O., Masson, F., Turner, D., and Weckwerth, T.: Mesoscale GPS tomography applied to the 12 June 2002 convective initiation event of IHOP 2002, Q. J. Roy. Meteor. Soc., 135, 645–662, https://doi.org/10.1002/qj.386, 2009.
Chen, B. and Liu, Z.: Voxel-optimized regional water vapor tomography and comparison with radiosonde and numerical weather model, J. Geod., https://doi.org/10.1007/s00190-014-0715-y, 2014.
Cucurull, L., Navascues, B., Ruffini, G., Elosegui, P., Rius, A., and Vila, J.: The use of GPS to validate NWP systems: the HIRLAM model, J. Atmos. Ocean. Tech., 17, 773–787, https://doi.org/10.1175/1520-0426(2000)017<0773:TUOGTV>2.0.CO;2, 2000.
Cucurull, L., van den Berghe, F., Barker, D., Vilaclara, E., and Rius, A.: Three-Dimensional Variational Data Assimilation of Ground-Based GPS ZTD and Meteorological Observations during the 14 December 2001 Storm Event over the Western Mediterranean Sea, Mon. Weather Rev., 132, 749–763, https://doi.org/10.1175/1520-0493(2004)132<0749:TVDAOG>2.0.CO;2, 2004.
Dach, R., Böhm, J., Lutz, S., Steigenberger, P., and Beutler, G.: Evaluation of the impact of atmospheric pressure loading modeling on GNSS data analysis, J. Geod., 85, 75–91, https://doi.org/10.1007/s00190-010-0417-z, 2011a.
Dach, R., Schmid, R., Schmitz, M., Thaller, D., Schaer, S., Lutz, S., Steigenberger, P., Wuebbena, G., and Beutler, G.: Improved antenna phase center models for GLONASS, J. Geod., 15, 49–65, https://doi.org/10.1007/s10291-010-0169-5, 2011b.
Davis, J., Herring, T., Shapiro, I., Rogers, A., and Elgered, G.: Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length, Radio Sci., 20, 1593–1607, https://doi.org/10.1029/RS020i006p01593, 1985.
de Haan, S.: Meteorological applications of a surface network of Global Positioning System receivers, PhD thesis, Wageningen Universiteit, the Netherlands, available at: https://www.knmi.nl/kennis-en-datacentrum/publicatie/meteorological-applications-of-a-surface-network-of-global-positioning-system-receivers, 2008.
de Haan, S.: Assimilation of GNSS ZTD and radar radial velocity for the benefit of very-short-range regional weather forecasts, Q. J. Roy. Meteor. Soc., 2097–2107, https://doi.org/10.1002/qj.2087, 2013.
de Haan, S., van der Marel, H., and Barlag, S.: Comparison of GPS slant delay measurements to a numerical model: case study for a cold front passage, Phys. Chem. Earth, 27, 317–322, https://doi.org/10.1016/S1474-7065(02)00006-2, 2002.
Dick, G., Gendt, G., and Reigber, C.: First Experience with Near Real-Time Water Vapor Estimation in a German GPS Network, J. Atmos. Sol.-Terr. Phy., 63, 1295–1304, https://doi.org/10.1016/S1364-6826(00)00248-0, 2001.
Douša, J.: Towards an Operational Near-real Time Precipitable Water Vapor Estimation, Phys. Chem. Earth Pt. A, 26, 189–194, https://doi.org/10.1016/S1464-1895(01)00045-X, 2001a.
Douša, J.: The Impact of Ultra-Rapid Orbits on Precipitable Water Vapor Estimation using Ground GPS Network, Phys. Chem. Earth Pt. A, 26, 393–398, https://doi.org/10.1016/S1464-1895(01)00072-2, 2001b.
Douša, J.: Precise near real-time GNSS analyses at Geodetic Observatory Pecny – precise orbit determination and water vapour monitoring, Acta Geodyn. Geomater., 7, 7–18, 2010.
Douša, J. and Bennitt, G. V.: Estimation and evaluation of hourly updated global GPS Zenith Total Delays over ten months, GPS Solutions, 17, 453–464, https://doi.org/10.1007/s10291-012-0291-7, 2013.
Douša, J. and Vaclavovic, P.: Real-time zenith tropospheric delays in support of numerical weather prediction applications, Adv. Space Res., 53, 1347–1358, https://doi.org/10.1016/j.asr.2014.02.021, 2014.
Dow, J. M., Neilan, R. E., and Rizos, C.: The International GNSS Service in a Changing Landscape of Global Navigation Satellite Systems, J. Geod., 83, 191–198, https://doi.org/10.1007/s00190-008-0300-3, 2009.
Elgered, G., Plag, H., Marel, H. V. D., Barlag, S., and Nash, J.: Exploitation of Ground-based GPS for Operational Numerical Weather Prediction and Climate Applications – Final Report, EU Publications Office (OPOCE), 234 pp., ISBN: 92-898-0012-7, 2005.
Eresmaa, R., Järvinen, H., Niemelä, S., and Salonen, K.: Asymmetricity of ground-based GPS slant delay data, Atmos. Chem. Phys., 7, 3143–3151, https://doi.org/10.5194/acp-7-3143-2007, 2007.
Eresmaa, R., Salonen, K., and Järvinen, H.: An observing-system experiment with ground-based GPS zenith total delay data using HIRLAM 3D-Var in the absence of satellite data, Q. J. Roy. Meteor. Soc., 136, 1289–1300, https://doi.org/10.1002/qj.632, 2010.
Faccani, C., Ferretti, R., Pacione, R., Paolucci, T., Vespe, F., and Cucurull, L.: Impact of a high density GPS network on the operational forecast, Adv. Geosci., 2, 73–79, https://doi.org/10.5194/adgeo-2-73-2005, 2005.
Field, C., Barros, V., Stocker, T. F., Qin, D., Dokken, D. J., Ebi, K. L., Mastrandrea, M., Mach, K., Plattner, G., Allen, S., Tignor, M., and Midgley, P.: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, New York, NY, USA, available at: https://www.ipcc.ch/pdf/special-reports/srex/SREX_Full_Report.pdf, 2012.
Flores, A., Rius, A., de Arellano, J. V.-G., and Escudero, A.: Spatio-temporal tomography of the lower troposphere using GPS signals, Phys. Chem. Earth Pt. A, 26, 405–411, https://doi.org/10.1016/S1464-1895(01)00074-6, 2001.
Foelsche, U. and Kirchengast, G.: Tropospheric water vapor imaging by combination of ground-based and spaceborne GNSS sounding data, J. Geophys. Res., 106, 221–27, https://doi.org/10.1029/2001JD900230, 2001.
Gaffen, D. J., Elliott, W., and Robock, A.: Relationships between tropospheric water vapor and surface temperature as observed by radiosondes, Geophys. Res. Lett., 19, 1839–1842, https://doi.org/10.1029/92GL02001, 1992.
Gendt, G.: IGS combination of tropospheric estimates – The pilot experiment, 1997 technical reports, IGS, JPL, Pasadena, California, USA, available at: ftp://igscb.jpl.nasa.gov/igscb/resource/pubs/pil_proj255-292.pdf, 1998.
Gendt, G., Reigber, C., and Dick, G.: Near Real-Time Water Vapor Estimation in a German GPS Network – Results from the Ground Program of HGF GASP Project, Phys. Chem. Earth Pt. A, 26, 413–416, https://doi.org/10.1016/S1464-1895(01)00075-8, 2001.
Gendt, G., Dick, G., Reigber, C., Tomassini, M., Liu, Y., and Ramatschi, M.: Near real time GPS water vapor monitoring for numerical weather prediction in Germany, J. Meteor. Soc. Jpn., 82, 361–370, https://doi.org/10.2151/jmsj.2004.361, 2004.
Gradinarsky, L. P., Johansson, J., Bouma, H. R., Scherneck, H. G., and Elgered, G.: Climate monitoring using GPS, Phys. Chem. Earth, 27, 335–340, https://doi.org/10.1016/S1474-7065(02)00009-8, 2002.
Graham, E., Koffi, E. N., and Matzler, C.: An observational study of air and water vapour convergence over the western Alps during summer and the development of isolated thunderstorms, Meteorol. Z., 21, 1–13, https://doi.org/10.1127/0941-2948/2012/0347, 2012.
Guerova, G. and Tomassini, M.: Monitoring IWV from GPS and limited – area forecast model, Tech. Rep. 2003–15, University of Bern, Switzerland, available at: http://www.iap.unibe.ch/publications/pub-detail.php?lang=en&id=729, September 2003.
Guerova, G., Brockmann, E., Quiby, J., Schubiger, F., and Matzler, C.: Validation of NWP mesoscale models with Swiss GPS Network AGNES, J. App. Meteorol., 42, 141–150, https://doi.org/10.1175/1520-0450(2003)042<0141:VONMMW>2.0.CO;2, 2003.
Guerova, G., Bettems, J.-M., Brockmann, E., and Matzler, C.: Assimilation of the GPS-derived Integrated Water Vapour (IWV) in the MeteoSwiss Numerical Weather Prediction model – a first experiment, Phys. Chem. Earth, 29, 177–186, https://doi.org/10.1016/j.pce.2004.01.009, 2004.
Guerova, G., Brockmann, E., Schubiger, F., Morland, J., and Matzler, C.: An integrated assessment of measured and modeled IWV in Switzerland for the period 2001–2003, J. App. Meteorol., 44, 1033–1044, https://doi.org/10.1175/JAM2255.1, 2005.
Guerova, G., Bettems, J.-M., Brockmann, E., and Matzler, C.: Assimilation of COST 716 Near Real Time GPS data in the nonhydrostatic limited area model used at MeteoSwiss, Meteorol. Atmos. Phys., 91, 149–164, https://doi.org/10.1007/s00703-005-0110-6, 2006.
Haase, J., Calais, E., Talaya, J., Rius, A., Vespe, F., Santangelo, R., Huang, X.-Y., Davila, J. M., Ge, M., Cucurull, L., Flores, A., Sciarretta, C., Pacione, R., Boccolari, M., Pugnaghi, S., Vedel, H., Mogensen, K., Yang, X., and Garate, J.: The contributions of the MAGIC project to the COST 716 objectives of assessing the operational potential of ground-based GPS meteorology on an international scale, Phys. Chem. Earth Pt. A, 26, 433–437, https://doi.org/10.1016/S1464-1895(01)00079-5, 2001.
Haase, J., Ge, M., Vedel, H., and Calais, E.: Accuracy and variability of GPS tropospheric delay measurements of water vapor in the western Mediterranean, J. App. Meteorol., 42, 1547–1568, https://doi.org/10.1175/1520-0450(2003)042<1547:AAVOGT>2.0.CO;2, 2003.
Heise, S., Dick, G., Gendt, G., Schmidt, T., and Wickert, J.: Integrated water vapor from IGS ground-based GPS observations: initial results from a global 5-min data set, Ann. Geophys., 27, 2851–2859, https://doi.org/10.5194/angeo-27-2851-2009, 2009.
Held, I. M. and Soden, B. J.: Robust responses of the hydrological cycle to global warming, J. Clim., 19, 5686–5699, https://doi.org/10.1175/JCLI3990.1, 2006.
Henriksen, S. W., Mancini, A., and Chovitz, B. H. (Eds.): The Use of Artificial Satellites for Geodesy, American Geophysical Union, Washington, DC, https://doi.org/10.1029/GM015p0247, 1972.
Jarlemark, P., Emardson, R., Johansson, J., and Elgered, G.: Ground-Based GPS for Validation of Climate Models: The Impact of Satellite Antenna Phase Center Variations, IEEE T. Geosci. Remote, 48, 3847–3854, https://doi.org/10.1109/TGRS.2010.2049114, 2010.
Järvinen, H., Eresmaa, R., Vedel, H., Salonen, K., Niemelä, S., and de Vries, J.: A variational data assimilation system for ground-based GPS slant delays, Q. J. Roy. Meteor. Soc., 133, 969–980, https://doi.org/10.1002/qj.79, 2007.
Jin, S. G., Luo, O. F., and Gleason, S.: Characterization of diurnal cycles in ZTD from a decade of global GPS observation, J. Geod., 83, 537–545, https://doi.org/10.1007/s00190-008-0264-3, 2009.
Johansson, J. M., Emardson, T. R., Jarlemark, P. O. J., Gradinarsky, L. P., and Elgered, G.: The atmospheric influence on the results from the Swedish GPS network, Phys. Chem. Earth, 23, 107–112, https://doi.org/10.1016/S0079-1946(97)00251-6, 1998.
Kačmařík, M. and Rapant, L.: New GNSS tomography of the atmosphere method – proposal and testing, in: Geoinformatics, edited by: Čepek, A., Czech Technical University, 9, 63–76, http://geoinformatics.fsv.cvut.cz/pdf/geoinformatics-fce-ctu-2012-09.pdf, 2012.
Kačmařík, M., Douša, J., and Zapletal, J.: Comparison of GPS slant wet delays acquired by different techniques, Acta Geodyn. Geomater., 9, 427–433, 2012.
Keernik, H., Ohvrila, H., Jakobsona, E., Rannat, K., and Luhamaaa, A.: Column water vapour: an intertechnique comparison of estimation methods in Estonia, P. Est. Acad. Sci., 63, 37–47, https://doi.org/10.3176/proc.2014.1.07, 2014.
Kehrer, K., Graf, B., and Roeder, W. P.: Global positioning system (GPS) precipitable water in forecasting lightning at spaceport Canaveral, Weather Forecast., 23, 219–232, https://doi.org/10.1175/2007WAF2006105.1, 2008.
Köpken, C.: Validation of integrated water vapor from numerical models using ground-based GPS, SSM/I, and water vapor radiometer measurements, J. App. Meteorol., 40, 1105–1117, https://doi.org/10.1175/1520-0450(2001)040<1105:VOIWVF>2.0.CO;2, 2001.
Labbouz, L., Baelen, J. V., Tridon, F., Reverdy, M., Hagen, M., Bender, M., Dick, G., and Gorgas, T.: Precipitation on the lee side of the Vosges Mountains: Multi-instrumental study of one case from the COPS campaign, Meteorol. Z., 22, 413–432, https://doi.org/10.1127/0941-2948/2013/0413, 2013.
Li, M., Li, W., Shi, C., Zhao, Q., Su, X., Qu, L., and Liu, Z.: Assessment of Precipitable Water Vapor Derived from Ground-based BeiDou Observations with Precise Point Positioning Approach, Adv. Space Res., https://doi.org/10.1016/j.asr.2014.10.010, 2014a.
Li, X., Dick, G., Ge, M., Heise, S., Wickert, J., and Bender, M.: Real-time GPS sensing of atmospheric water vapor: precise point positioning with orbit, clock and phase delay corrections, Geophys. Res. Lett., 41, 3615–3621, https://doi.org/10.1002/2013GL058721, 2014b.
Mahfouf, J.-F., Boullut, N., Moll, P., Payan, C., Wattrelot, E., Augros, C., and Caumont, O.: Observation usage in Meteo France data assimilation systems: Current status and planned evolutions, Aladin workshop presentation, available at: http://www.cnrm.meteo.fr/aladin/IMG/pdf/mahfouf.pdf, 2012.
Manning, T., Zhang, K., Rohm, W., Choy, S., and Hurter, F.: Detecting Severe Weather using GPS Tomography: An Australian Case Study, J. Glob. Positioning Syst., 11, 58–70, available at: http://www.gnss.com.au/JoGPS/v11n1/JoGPS_v11n1p58-70.pdf, 2012.
Mazany, R., Businger, S., and Gutman, S.: A lightning prediction index that utilizes GPS integrated precipitable water vapor, Weather Forecast., 17, 1034–1047, https://doi.org/10.1175/1520-0434(2002)017<1034:ALPITU>2.0.CO;2, 2002.
Miidla, P., Rannat, K., and Uba, P.: Tomographic approach for tropospheric water vapour detection, Comput. Meth. Appl. Math., 8, 263–278, https://doi.org/10.2478/cmam-2008-0019, 2008.
Moll, P., Poli, P., and Ducrocq, V.: Use of ground based GNSS data in NWP at Météo-France, e-GVAP expert team meeting, html://egvap.dmi.dk/workshop/5-assimilation-meteo-france-Moll.pdf, 2008.
Morland, J., Collaud Coen, M., Hocke, K., Jeannet, P., and Mätzler, C.: Tropospheric water vapour above Switzerland over the last 12 years, Atmos. Chem. Phys., 9, 5975–5988, https://doi.org/10.5194/acp-9-5975-2009, 2009.
Nilsson, T. and Elgered, G.: Long-term trends in the atmospheric water vapor content estimated from ground-based GPS data, J. Geophys. Res., 113, D19101, https://doi.org/10.1029/2008JD010110, 2008.
Nilsson, T., Gradinarsky, L., and Elgered, G.: Water vapour tomography using GPS phase observations: Results from the ESCOMPTE experiment, Tellus A, 59, 674–682, https://doi.org/10.1111/j.1600-0870.2007.00247.x, 2007.
Ning, T. and Elgered, G.: Trends in the atmospheric water vapor content from ground-based GPS: the impact of the elevation cutoff angle, IEEE J. Sel. Top. Appl., 5, 744–751, https://doi.org/10.1109/JSTARS.2012.2191392, 2012.
Ning, T., Haas, R., Elgered, G., and Willén, U.: Multi-technique comparisons of ten years of wet delay estimates on the west coast of Sweden, J. Geod., 86, 565–575, https://doi.org/10.1007/s00190-011-0527-2, 2012.
Ning, T., Elgered, G., Willen, U., and Johansson, J. M.: Evaluation of the atmospheric water vapor content in a regional climate model using ground-based GPS measurements, J. Geophys. Res., 118, 1–11, https://doi.org/10.1029/2012JD018053, 2013.
Notarpietro, R., Cucca, M., Gabella, M., Venuti, G., and Perona, G.: Tomographic reconstruction of Wet and Total Refractivity fields from GNSS receiver networks, Adv. Space Res., 47, 769–912, https://doi.org/10.1016/j.asr.2010.12.025, 2011.
Perler, D., Geiger, A., and Hurter, F.: 4D GPS water vapor tomography: new parameterized approaches, J. Geod., 85, 539–550, https://doi.org/10.1007/s00190-011-0454-2, 2011.
Poli, P., Moll, P., Rabier, F., Desroziers, G., Chapnik, B., Berre, L., Healy, S. B., Andersson, E., and Guelai, F.-Z. E.: Forecast impact studies of zenith total delay data from European near real-time GPS stations in Meteo France 4DVAR, J. Geophys. Res., 112, D06114, https://doi.org/10.1029/2006JD007430, 2007.
Pottiaux, E., Bruyninx, C., Brockmann, E., and Söhne, W.: The EUREF-EUMETNET Collaboration: First experience and Potential Benefits, Bollettino di geodesia e scienze affini, 68, 269–286, ISBN: 0006-6710, 2009.
Reverdy, M., Baelen, J. V., Walpersdorf, A., Dick, G., Hagen, M., and Richard, E.: Water vapor fields retrieve with tomography software, Ann. Meteo., 44, 144–145, 2009.
Rohm, W.: The ground GNSS tomography – unconstrained approach, Adv. Space Res., 51, 501–513, https://doi.org/10.1016/j.asr.2012.09.021, 2013.
Rohm, W., Zhang, K., and Bosy, J.: Limited constraint, robust Kalman filtering for GNSS troposphere tomography, Atmos. Meas. Tech., 7, 1475–1486, https://doi.org/10.5194/amt-7-1475-2014, 2014.
Ross, R. J. and Elliott, W. P.: Tropospheric water vapor climatology and trends over North America: 1973–93, J. Climate, 9, 3561–3574, https://doi.org/10.1175/1520-0442(1996)009<3561:TWVCAT>2.0.CO;2, 1996.
Ross, R. J. and Elliott, W. P.: Radiosonde based northern hemisphere tropospheric water vapor trends, J. Climate, 14, 1602–1612, https://doi.org/10.1175/1520-0442(2001)014<1602:RBNHTW>2.0.CO;2, 2001.
Saqellari-Likoka, A. and Karathanassi, V.: An Approach for Solving Rank-Deficient Systems That Enable Atmospheric Path Delay and Water Vapor Content Estimation, IEEE T. Geosci. Remote, 46, 3187–3195, https://doi.org/10.1109/TGRS.2008.921744, 2008.
Schwitalla, T., Bauer, H.-S., Wulfmeyer, V., and Zängl, G.: Systematic errors of QPF in low-mountain regions as revealed by MM5 simulations, Meteorol. Z., 17, 903–919, https://doi.org/10.1127/0941-2948/2008/0338, 2008.
Schwitalla, T., Bauer, H.-S., Wulfmeyer, V., and Aoshima, F.: High-resolution simulation over central Europe: assimilation experiments during COPS IOP 9c, Q. J. Roy. Meteor. Soc., 137, 156–175, https://doi.org/10.1002/qj.721, 2011.
Seco, A., Ramirez, F., Serna, E., Prieto, E., Garcia, R., Moreno, A., Cantera, J. C., Miqueleiz, L., and Priego, J. E.: Rain pattern analysis and forecast model based on GPS estimated atmospheric water vapor content, Atmos. Environ., 49, 85–93, https://doi.org/10.1016/j.atmosenv.2011.12.019, 2012.
Sohn, D.-H. and Cho, J.: Trend Analysis of GPS Precipitable Water Vapor Above South Korea Over the Last 10 years, J. Astron. Space Sci., 27, 231–238, https://doi.org/10.5140/JASS.2010.27.3.231, 2010.
Spänkuch, D., Gueldner, J., Steinhagen, H., and Bender, M.: Analysis of a dryline-like feature in northern Germany detected by ground-based microwave profiling, Meteorol. Z., 20, 409–421, https://doi.org/10.1127/0941-2948/2011/0222, 2011.
Steigenberger, P., Tesmer, V., Krügel, M., Thaller, D., Schmid, R., Vey, S., and Rothacher, M.: Comparisons of homogeneously reprocessed GPS and VLBI long time-series of troposphere zenith delays and gradients, J. Geod., 81, 503–514, https://doi.org/10.1007/s00190-006-0124-y, 2007.
Stocker, T. F., Qin, D., Plattner, G., Tignor, M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. (Eds.): Climate change 2013: the physical science basis. Intergovernmental panel on climate change, working group I Contribution to the IPCC fifth assessment report (AR5), Cambridge University Press Cambridge, UK, New York, https://doi.org/10.1017/CBO9781107415324, 2013.
Suparta, W. and Ali, M.: Nowcasting the lightning activity in Peninsular Malaysia using the GPS PWV during the 2009 inter-monsoons, Ann. Geophys., 57, A0217, https://doi.org/10.4401/ag-6373, 2014.
Szintai, S. and Mile, M.: Update of current status and plans of C-SRNWP, EUMETNET Obset expert team meeting, ECMWF, Reading, UK, 15–17 April, 2015.
Teke, K., Nilsson, T., Böhm, J., Hobiger, T., Steigenberger, P., Garcia-Espada, S., Haas, R., and Willis, P.: Troposphere delays from space geodetic techniques, water vapor radiometers, and numerical weather models over a series of continuous VLBI campaigns, J. Geod., 87, 981–1001, https://doi.org/10.1007/s00190-013-0662-z, 2013.
Tomassini, M., Gendt, G., Dick, G., Ramatschi, M., and Schraff, C.: Monitoring of integrated water vapor from ground-based GPS observations and their assimilation in a limited-area model, Phys. Chem. Earth, 27, 341–346, https://doi.org/10.1016/S1474-7065(02)00010-4, 2002.
Tralli, D. M. and Lichten, S. M.: Stochastic estimation of tropospheric path delays in Global Positioning System geodetic measurements, B. Géodésique, 64, 127–152, https://doi.org/10.1007/BF02520642, 1990.
Trenberth, K. E., Fasullo, J., and Smit, L.: Trends and variability in column-integrated atmospheric water vapor, Clim. Dynam., 24, 741–758, https://doi.org/10.1007/s00382-005-0017-4, 2005.
Troller, M., Geiger, A., Brockmann, E., Bettems, J.-M., Bürki, B., and Kahle, H.-G.: Tomographic determination of the spatial distribution of water vapor using GPS observations, Adv. Space Res., 37, 2211–2217, https://doi.org/10.1016/j.asr.2005.07.002, 2006a.
Troller, M., Geiger, A., Brockmann, E., and Kahle, H.-G.: Determination of the spatial and temporal variation of tropospheric water vapour using CGPS networks, Geophys. J. Int., 167, 509–520, https://doi.org/10.1111/j.1365-246X.2006.03101.x, 2006b.
Urquhart, L., Nievinski, F. G., and Santos, M. C.: Assessment of troposphere mapping functions using three-dimensional ray-tracing, GPS Solutions, 18, 345–354, https://doi.org/10.1007/s10291-013-0334-8, 2014.
van Baelen, J., Reverdy, M., Tridon, F., Labbouz, L., Dick, G., Bender, M., and Hagen, M.: On the relationship between water vapour and evolution and the life cycle of precipitation systems, Q. J. Roy. Meteor. Soc., 137, 204–223, https://doi.org/10.1002/qj.785, 2011.
van der Marel, H., Brockmann, E., de Haan S, S., Douša, J., Johansson, J., Gendt, G., Kristiansen, O., Offiler, D., Pacione, R., Rius, A., and Vespe, F.: COST-716 demonstration project for the near real-time estimation of integrated water vapour from GPS, Phys. Chem. Earth, 29, 187–199, https://doi.org/10.1016/j.pce.2004.01.001, 2004.
Van Malderen, R., Brenot, H., Pottiaux, E., Beirle, S., Hermans, C., De Mazière, M., Wagner, T., De Backer, H., and Bruyninx, C.: A multi-site intercomparison of integrated water vapour observations for climate change analysis, Atmos. Meas. Tech., 7, 2487–2512, https://doi.org/10.5194/amt-7-2487-2014, 2014.
Vedel, H. and Huang, X.-Y.: Impact of ground based GPS data on numerical weather prediction, J. Meteor. Soc. Jpn., 82, 459–472, https://doi.org/10.2151/jmsj.2004.459, 2004.
Vedel, H., Mogensen, K. S., and Huang, X.-Y.: Calculation of zenith delays from meteorological data comparison of NWP model, radiosonde and GPS delays, Phys. Chem. Earth Pt. A, 26, 497–502, https://doi.org/10.1016/S1464-1895(01)00091-6, 2001.
Vedel, H., Huang, X-Y and, J., Ge, M., and Calais, E.: Impact of GPS zenith tropospheric delay data on precipitation forecasts in Mediterranean France and Spain, Geophys. Res. Lett., 31, https://doi.org/10.1029/2003GL017715, 2004.
Vey, S., Dietrich, R., Fritsche, M., Ruelke, A., Steigenberger, P., and Rothacher, M.: On the homogeneity and interpretation of precipitable water time series derived from global GPS observations, J. Geophys. Res., 114, D10101, https://doi.org/10.1029/2008JD010415, 2009.
Vey, S., Dietrich, R., Rlke, A., Fritsche, M., Steigenberger, P., and Rothacher, M.: Validation of precipitable water vapor within the NCEP/DOE reanalysis using global GPS observations from one decade, J. Climate, 23, 1675–1695, https://doi.org/10.1175/2009JCLI2787.1, 2010.
Walpersdorf, A., Calais, E., Haase, J., Eymard, L., Desbois, M., and Vedel, H.: Atmospheric gradients estimated by GPS compared to a high resolution numerical weather prediction (NWP) model, Phys. Chem. Earth Pt. A, 26, 147–152, https://doi.org/10.1016/S1464-1895(01)00038-2, 2001.
Wang, J. and Zhang, L.: Systematic errors in global radiosonde precipitable water data from comparisons with ground-based GPS measurements, J. Climate, 21, 2218–2238, https://doi.org/10.1175/2007JCLI1944.1, 2008.
Wang, J., Zhang, L., Dai, A., van Hove, T., and van Baelen, J.: A near-global, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements, J. Geophys. Res., 112, D11107, https://doi.org/10.1029/2006JD007529, 2007.
Wang, J., Zhang, L., Dai, A., Immler, F., Sommer, M., and Voemel, H.: Radiation dry bias correction of Vaisala RS92 humidity data and its impacts on historical Radiosonde data, J. Atmos. Ocean. Tech., 30, 197–214, https://doi.org/10.1175/JTECH-D-12-00113.1, 2013.
Ware, R. H., Fulker, D. W., Stein, S. A., Anderson, D. N., Avery, S. K., Droegemeier, R. D. C. K. K., Kuettner, J. P., Minster, J., and Sorooshian, S.: Real-time national GPS networks: Opportunities for atmospheric sensing, Earth Planets Space, 52, 901–905, https://doi.org/10.1186/BF03352303, 2000.
Wentz, F. J. and Schabel, M.: Precise climate monitoring using complementary satellite data sets, Nature, 403, 414–416, https://doi.org/10.1038/35000184, 2000.
Yan, X., Ducrocq, V., Jaubert, G., Brousseau, P., Poli, P., Champollion, C., Flamant, C., and Boniface, K.: The benefit of GPS zenith delay assimilation to high-resolution quantitative precipitation forecasts: a case-study from COPS IOP 9, Q. J. Roy. Meteol. Soc., 135, 1788–1800, https://doi.org/10.1002/qj.508, 2009a.
Yan, X., Ducrocq, V., Poli, P., Hakam, M., Jaubert, G., and Walpersdorf, A.: Impact of GPS zenith delay assimilation on convective-scale prediction of Mediterranean heavy rainfall, J. Geophys. Res., 114, D03104, https://doi.org/10.1029/2008JD011036, 2009b.
Yang, H., Sass, B. H., Elgered, G., Johansson, J. M., and Emardson, T. R.: A comparison of precipitable water vapor estimates by an NWP simulation and GPS observations, J. App. Meteorol., 38, 941–956, https://doi.org/10.1175/1520-0450(1999)038<0941:ACOPWV>2.0.CO;2, 1999.
Yuan, Y., Zhang, K., Rohm, W., Choy, S., Norman, R., and Wang, C. S.: Real-time retrieval of precipitable water vapor from GPS precise point positioning, J. Geophys. Res., 119, 10044–10057, https://doi.org/10.1002/2014JD021486, 2014.
Zumberge, J. F., Heflin, M. B., Jefferson, D. C., Watkins, M. M., and Webb, F. H.: Precise Point Positioning for the efficient and robust analysis of GPS data from large networks, J. Geophys. Res., 102, 5005–5017, https://doi.org/10.1029/96JB03860, 1997.
Zus, F., Wickert, J., Bauer, H. S., Schwitalla, T., and Wulfmeyer, V.: Experiments of GPS slant path data assimilation with an advanced MM5 4DVAR system, Meteorol. Z., 20, 173–184, https://doi.org/10.1127/0941-2948/2011/0232, 2011.
Zus, F., Dick, G., Heise, S., and Wickert, J.: A forward operator and its adjoint for GPS slant total delays, Radio Sci., 50, 393–405, https://doi.org/10.1002/2014RS005584, 2015.
Short summary
Application of global navigation satellite systems (GNSSs) for atmospheric remote sensing (GNSS meteorology) is a well-established field in both research and operation in Europe. This review covers the state of the art in GNSS meteorology in Europe. It discusses 1) advances in GNSS processing techniques and tropospheric products, 2) use in numerical weather prediction and nowcasting, and 3) climate research.
Application of global navigation satellite systems (GNSSs) for atmospheric remote sensing (GNSS...
