Articles | Volume 13, issue 11
https://doi.org/10.5194/gmd-13-5757-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-5757-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
25 Nov 2020
Methods for assessment of models |
| 25 Nov 2020
| 25 Nov 2020
Multilayer cloud conditions in trade wind shallow cumulus – confronting two ICON model derivatives with airborne observations
Institute for Geophysics and Meteorology, University of Cologne, Albertus-Magnus-Platz, 50923 Cologne, Germany
Pavlos Kollias
Institute for Geophysics and Meteorology, University of Cologne, Albertus-Magnus-Platz, 50923 Cologne, Germany
School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000, USA
Felix Ament
Meteorological Institute, Universität Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany
Vera Schemann
Institute for Geophysics and Meteorology, University of Cologne, Albertus-Magnus-Platz, 50923 Cologne, Germany
Susanne Crewell
Institute for Geophysics and Meteorology, University of Cologne, Albertus-Magnus-Platz, 50923 Cologne, Germany
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Nitika Yadlapalli Yurk, Matthew Lebsock, Juan Socuellamos, Raquel Rodriguez Monje, Ken Cooper, and Pavlos Kollias
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Sarah Wugofski, Matthew R. Kumjian, Mariko Oue, and Pavlos Kollias
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Marco Coppola, Alessandro Battaglia, Frederic Tridon, and Pavlos Kollias
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Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
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Bernat Puigdomènech Treserras and Pavlos Kollias
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Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
The Cryosphere, 18, 4137–4163, https://doi.org/10.5194/tc-18-4137-2024, https://doi.org/10.5194/tc-18-4137-2024, 2024
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Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona M. Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schaefer, Vera Schemann, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
Atmos. Chem. Phys., 24, 8865–8892, https://doi.org/10.5194/acp-24-8865-2024, https://doi.org/10.5194/acp-24-8865-2024, 2024
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The Arctic is warming faster than the rest of the globe. Warm-air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold-air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to mid-latitude weather. In our article, we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented with state-of-the-art remote-sensing and in situ measurement devices.
Henning Dorff, Heike Konow, Vera Schemann, and Felix Ament
Atmos. Chem. Phys., 24, 8771–8795, https://doi.org/10.5194/acp-24-8771-2024, https://doi.org/10.5194/acp-24-8771-2024, 2024
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Andreas Walbröl, Janosch Michaelis, Sebastian Becker, Henning Dorff, Kerstin Ebell, Irina Gorodetskaya, Bernd Heinold, Benjamin Kirbus, Melanie Lauer, Nina Maherndl, Marion Maturilli, Johanna Mayer, Hanno Müller, Roel A. J. Neggers, Fiona M. Paulus, Johannes Röttenbacher, Janna E. Rückert, Imke Schirmacher, Nils Slättberg, André Ehrlich, Manfred Wendisch, and Susanne Crewell
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To support the interpretation of the data collected during the HALO-(AC)3 campaign, which took place in the North Atlantic sector of the Arctic from 7 March to 12 April 2022, we analyze how unusual the weather and sea ice conditions were with respect to the long-term climatology. From observations and ERA5 reanalysis, we found record-breaking warm air intrusions and a large variety of marine cold air outbreaks. Sea ice concentration was mostly within the climatological interquartile range.
Robin J. Hogan, Anthony J. Illingworth, Pavlos Kollias, Hajime Okamoto, and Ulla Wandinger
Atmos. Meas. Tech., 17, 3081–3083, https://doi.org/10.5194/amt-17-3081-2024, https://doi.org/10.5194/amt-17-3081-2024, 2024
Kristofer S. Tuftedal, Bernat Puigdomènech Treserras, Mariko Oue, and Pavlos Kollias
Atmos. Chem. Phys., 24, 5637–5657, https://doi.org/10.5194/acp-24-5637-2024, https://doi.org/10.5194/acp-24-5637-2024, 2024
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This study analyzed coastal convective cells from June through September 2018–2021. The cells were classified and their lifecycles were analyzed to better understand their characteristics. Features such as convective-core growth, for example, are shown. The study found differences in the initiation location of shallow convection and in the aerosol loading in deep convective environments. This work provides a foundation for future analyses of convection or other tracked events elsewhere.
Finn Burgemeister, Marco Clemens, and Felix Ament
Earth Syst. Sci. Data, 16, 2317–2332, https://doi.org/10.5194/essd-16-2317-2024, https://doi.org/10.5194/essd-16-2317-2024, 2024
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Knowledge of small-scale rainfall variability is needed for hydro-meteorological applications in urban areas. Therefore, we present an open-access data set covering reanalyzed radar reflectivities and rainfall estimates measured by a weather radar at high spatio-temporal resolution in the urban environment of Hamburg between 2013 and 2021. We describe the data reanalysis, outline the measurement’s performance for long time periods, and discuss open issues and limitations of the data set.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Zeen Zhu, Fan Yang, Pavlos Kollias, Raymond A. Shaw, Alex B. Kostinski, Steve Krueger, Katia Lamer, Nithin Allwayin, and Mariko Oue
Atmos. Meas. Tech., 17, 1133–1143, https://doi.org/10.5194/amt-17-1133-2024, https://doi.org/10.5194/amt-17-1133-2024, 2024
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In this article, we demonstrate the feasibility of applying advanced radar technology to detect liquid droplets generated in the cloud chamber. Specifically, we show that using radar with centimeter-scale resolution, single drizzle drops with a diameter larger than 40 µm can be detected. This study demonstrates the applicability of remote sensing instruments in laboratory experiments and suggests new applications of ultrahigh-resolution radar for atmospheric sensing.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
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When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
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This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
Giovanni Chellini, Rosa Gierens, Kerstin Ebell, Theresa Kiszler, Pavel Krobot, Alexander Myagkov, Vera Schemann, and Stefan Kneifel
Earth Syst. Sci. Data, 15, 5427–5448, https://doi.org/10.5194/essd-15-5427-2023, https://doi.org/10.5194/essd-15-5427-2023, 2023
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We present a comprehensive quality-controlled dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region, and substantially warm the surface. However, our understanding of microphysical processes in these clouds is incomplete. This dataset includes a comprehensive set of variables which allow for extensive investigation of such processes in LLMPCs at the site.
David P. Donovan, Pavlos Kollias, Almudena Velázquez Blázquez, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5327–5356, https://doi.org/10.5194/amt-16-5327-2023, https://doi.org/10.5194/amt-16-5327-2023, 2023
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The Earth Cloud, Aerosol and Radiation Explorer mission (EarthCARE) is a multi-instrument cloud–aerosol–radiation-oriented satellite for climate and weather applications. For this satellite mission to be successful, the development and implementation of new techniques for turning the measured raw signals into useful data is required. This paper describes how atmospheric model data were used as the basis for creating realistic high-resolution simulated data sets to facilitate this process.
Imke Schirmacher, Pavlos Kollias, Katia Lamer, Mario Mech, Lukas Pfitzenmaier, Manfred Wendisch, and Susanne Crewell
Atmos. Meas. Tech., 16, 4081–4100, https://doi.org/10.5194/amt-16-4081-2023, https://doi.org/10.5194/amt-16-4081-2023, 2023
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CloudSat’s relatively coarse spatial resolution, low sensitivity, and blind zone limit its assessment of Arctic low-level clouds, which affect the surface energy balance. We compare cloud fractions from CloudSat and finely resolved airborne radar observations to determine CloudSat’s limitations. Cloudsat overestimates cloud fractions above its blind zone, especially during cold-air outbreaks over open water, and misses a cloud fraction of 32 % and half of the precipitation inside its blind zone.
Amelie U. Schmitt, Felix Ament, Alessandro C. de Araújo, Marta Sá, and Paulo Teixeira
Atmos. Chem. Phys., 23, 9323–9346, https://doi.org/10.5194/acp-23-9323-2023, https://doi.org/10.5194/acp-23-9323-2023, 2023
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Tall vegetation in forests affects the exchange of heat and moisture between the atmosphere and the land surface. We compared measurements from the Amazon Tall Tower Observatory to results from a land surface model to identify model shortcomings. Our results suggest that soil temperatures in the model could be improved by incorporating a separate canopy layer which represents the heat storage within the forest.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
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We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Melanie Lauer, Annette Rinke, Irina Gorodetskaya, Michael Sprenger, Mario Mech, and Susanne Crewell
Atmos. Chem. Phys., 23, 8705–8726, https://doi.org/10.5194/acp-23-8705-2023, https://doi.org/10.5194/acp-23-8705-2023, 2023
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We present a new method to analyse the influence of atmospheric rivers (ARs), cyclones, and fronts on the precipitation in the Arctic, based on two campaigns: ACLOUD (early summer 2017) and AFLUX (early spring 2019). There are differences between both campaign periods: in early summer, the precipitation is mostly related to ARs and fronts, especially when they are co-located, while in early spring, cyclones isolated from ARs and fronts contributed most to the precipitation.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
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We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Pavlos Kollias, Bernat Puidgomènech Treserras, Alessandro Battaglia, Paloma C. Borque, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 1901–1914, https://doi.org/10.5194/amt-16-1901-2023, https://doi.org/10.5194/amt-16-1901-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission developed by the European Space Agency (ESA) and Japan Aerospace Exploration Agency (JAXA) features the first spaceborne 94 GHz Doppler cloud-profiling radar (CPR) with Doppler capability. Here, we describe the post-processing algorithms that apply quality control and corrections to CPR measurements and derive key geophysical variables such as hydrometeor locations and best estimates of particle sedimentation fall velocities.
Zackary Mages, Pavlos Kollias, Zeen Zhu, and Edward P. Luke
Atmos. Chem. Phys., 23, 3561–3574, https://doi.org/10.5194/acp-23-3561-2023, https://doi.org/10.5194/acp-23-3561-2023, 2023
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Cold-air outbreaks (when cold air is advected over warm water and creates low-level convection) are a dominant cloud regime in the Arctic, and we capitalized on ground-based observations, which did not previously exist, from the COMBLE field campaign to study them. We characterized the extent and strength of the convection and turbulence and found evidence of secondary ice production. This information is useful for model intercomparison studies that will represent cold-air outbreak processes.
Mariko Oue, Stephen M. Saleeby, Peter J. Marinescu, Pavlos Kollias, and Susan C. van den Heever
Atmos. Meas. Tech., 15, 4931–4950, https://doi.org/10.5194/amt-15-4931-2022, https://doi.org/10.5194/amt-15-4931-2022, 2022
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This study provides an optimization of radar observation strategies to better capture convective cell evolution in clean and polluted environments as well as a technique for the optimization. The suggested optimized radar observation strategy is to better capture updrafts at middle and upper altitudes and precipitation particle evolution of isolated deep convective clouds. This study sheds light on the challenge of designing remote sensing observation strategies in pre-field campaign periods.
Bastian Kirsch, Cathy Hohenegger, Daniel Klocke, Rainer Senke, Michael Offermann, and Felix Ament
Earth Syst. Sci. Data, 14, 3531–3548, https://doi.org/10.5194/essd-14-3531-2022, https://doi.org/10.5194/essd-14-3531-2022, 2022
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Conventional observation networks are too coarse to resolve the horizontal structure of kilometer-scale atmospheric processes. We present the FESST@HH field experiment that took place in Hamburg (Germany) during summer 2020 and featured a dense network of 103 custom-built, low-cost weather stations. The data set is capable of providing new insights into the structure of convective cold pools and the nocturnal urban heat island and variations of local temperature fluctuations.
Henning Dorff, Heike Konow, and Felix Ament
Atmos. Meas. Tech., 15, 3641–3661, https://doi.org/10.5194/amt-15-3641-2022, https://doi.org/10.5194/amt-15-3641-2022, 2022
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This study elaborates how aircraft-based horizontal geometries of trade wind cumuli differ whether a one-dimensional profiling radar or a two-dimensional imager is used. Cloud size distributions are examined in terms of sensitivity to sample size, resolution, and instrument field of view. While the radar cannot reproduce the double power law distribution due to coarse resolution and restriction to vertical transects, the imager also reveals the elliptic cloud structure enhancing with wind speed.
Zeen Zhu, Pavlos Kollias, Edward Luke, and Fan Yang
Atmos. Chem. Phys., 22, 7405–7416, https://doi.org/10.5194/acp-22-7405-2022, https://doi.org/10.5194/acp-22-7405-2022, 2022
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Drizzle (small rain droplets) is an important component of warm clouds; however, its existence is poorly understood. In this study, we capitalized on a machine-learning algorithm to develop a drizzle detection method. We applied this algorithm to investigate drizzle occurrence and found out that drizzle is far more ubiquitous than previously thought. This study demonstrates the ubiquitous nature of drizzle in clouds and will improve understanding of the associated microphysical process.
Annakaisa von Lerber, Mario Mech, Annette Rinke, Damao Zhang, Melanie Lauer, Ana Radovan, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 7287–7317, https://doi.org/10.5194/acp-22-7287-2022, https://doi.org/10.5194/acp-22-7287-2022, 2022
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Snowfall is an important climate indicator. However, microphysical snowfall processes are challenging for atmospheric models. In this study, the performance of a regional climate model is evaluated in modeling the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations. Excellent agreement in averaged annual snowfall rates is found, and the shown methodology offers a promising diagnostic tool to investigate the shown differences further.
Alessandro Battaglia, Paolo Martire, Eric Caubet, Laurent Phalippou, Fabrizio Stesina, Pavlos Kollias, and Anthony Illingworth
Atmos. Meas. Tech., 15, 3011–3030, https://doi.org/10.5194/amt-15-3011-2022, https://doi.org/10.5194/amt-15-3011-2022, 2022
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We present an instrument simulator for a new sensor, WIVERN (WInd VElocity Radar Nephoscope), a conically scanning radar payload with Doppler capabilities, recently down-selected as one of the four candidates for the European Space Agency Earth Explorer 11 program. The mission aims at measuring horizontal winds in cloudy areas. The simulator is instrumental in the definition and consolidation of the mission requirements and the evaluation of mission performances.
Carolina Viceto, Irina V. Gorodetskaya, Annette Rinke, Marion Maturilli, Alfredo Rocha, and Susanne Crewell
Atmos. Chem. Phys., 22, 441–463, https://doi.org/10.5194/acp-22-441-2022, https://doi.org/10.5194/acp-22-441-2022, 2022
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We focus on anomalous moisture transport events known as atmospheric rivers (ARs). During ACLOUD and PASCAL, three AR events were identified: 30 May, 6 June, and 9 June 2017. We explore their spatio-temporal evolution and precipitation patterns using measurements, reanalyses, and a model. We show the importance of the following: Atlantic and Siberian pathways during spring–summer in the Arctic, AR-associated heat/moisture increase, precipitation phase transition, and high-resolution datasets.
Claudia Acquistapace, Richard Coulter, Susanne Crewell, Albert Garcia-Benadi, Rosa Gierens, Giacomo Labbri, Alexander Myagkov, Nils Risse, and Jan H. Schween
Earth Syst. Sci. Data, 14, 33–55, https://doi.org/10.5194/essd-14-33-2022, https://doi.org/10.5194/essd-14-33-2022, 2022
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This publication describes the unprecedented high-resolution cloud and precipitation dataset collected by two radars deployed on the Maria S. Merian research vessel. The ship operated in the west Atlantic Ocean during the measurement campaign called EUREC4A, between 19 January and 19 February 2020. The data collected are crucial to investigate clouds and precipitation and understand how they form and change over the ocean, where it is so difficult to measure them.
Hélène Bresson, Annette Rinke, Mario Mech, Daniel Reinert, Vera Schemann, Kerstin Ebell, Marion Maturilli, Carolina Viceto, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 173–196, https://doi.org/10.5194/acp-22-173-2022, https://doi.org/10.5194/acp-22-173-2022, 2022
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Arctic warming is pronounced, and one factor in this is the poleward atmospheric transport of heat and moisture. This study assesses the 4D structure of an Arctic moisture intrusion event which occurred in June 2017. For the first time, high-resolution pan-Arctic ICON simulations are performed and compared with global models, reanalysis, and observations. Results show the added value of high resolution in the event representation and the impact of the intrusion on the surface energy fluxes.
Heike Konow, Florian Ewald, Geet George, Marek Jacob, Marcus Klingebiel, Tobias Kölling, Anna E. Luebke, Theresa Mieslinger, Veronika Pörtge, Jule Radtke, Michael Schäfer, Hauke Schulz, Raphaela Vogel, Martin Wirth, Sandrine Bony, Susanne Crewell, André Ehrlich, Linda Forster, Andreas Giez, Felix Gödde, Silke Groß, Manuel Gutleben, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Theresa Lang, Bernhard Mayer, Mario Mech, Marc Prange, Sabrina Schnitt, Jessica Vial, Andreas Walbröl, Manfred Wendisch, Kevin Wolf, Tobias Zinner, Martin Zöger, Felix Ament, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 5545–5563, https://doi.org/10.5194/essd-13-5545-2021, https://doi.org/10.5194/essd-13-5545-2021, 2021
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The German research aircraft HALO took part in the research campaign EUREC4A in January and February 2020. The focus area was the tropical Atlantic east of the island of Barbados. We describe the characteristics of the 15 research flights, provide auxiliary information, derive combined cloud mask products from all instruments that observe clouds on board the aircraft, and provide code examples that help new users of the data to get started.
Sonja Drueke, Daniel J. Kirshbaum, and Pavlos Kollias
Atmos. Chem. Phys., 21, 14039–14058, https://doi.org/10.5194/acp-21-14039-2021, https://doi.org/10.5194/acp-21-14039-2021, 2021
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This numerical study provides insights into the sensitivity of shallow-cumulus dilution to geostrophic vertical wind profile. The cumulus dilution is strongly sensitive to vertical wind shear in the cloud layer, with shallow cumuli being more diluted in sheared environments. On the other hand, wind shear in the subcloud layer leads to less diluted cumuli. The sensitivities are explained by jointly considering the impacts of vertical velocity and the properties of the entrained air.
Bernd Schalge, Gabriele Baroni, Barbara Haese, Daniel Erdal, Gernot Geppert, Pablo Saavedra, Vincent Haefliger, Harry Vereecken, Sabine Attinger, Harald Kunstmann, Olaf A. Cirpka, Felix Ament, Stefan Kollet, Insa Neuweiler, Harrie-Jan Hendricks Franssen, and Clemens Simmer
Earth Syst. Sci. Data, 13, 4437–4464, https://doi.org/10.5194/essd-13-4437-2021, https://doi.org/10.5194/essd-13-4437-2021, 2021
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In this study, a 9-year simulation of complete model output of a coupled atmosphere–land-surface–subsurface model on the catchment scale is discussed. We used the Neckar catchment in SW Germany as the basis of this simulation. Since the dataset includes the full model output, it is not only possible to investigate model behavior and interactions between the component models but also use it as a virtual truth for comparison of, for example, data assimilation experiments.
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.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
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Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
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Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
Katia Lamer, Mariko Oue, Alessandro Battaglia, Richard J. Roy, Ken B. Cooper, Ranvir Dhillon, and Pavlos Kollias
Atmos. Meas. Tech., 14, 3615–3629, https://doi.org/10.5194/amt-14-3615-2021, https://doi.org/10.5194/amt-14-3615-2021, 2021
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Observations collected during the 25 February 2020 deployment of the VIPR at the Stony Brook Radar Observatory clearly demonstrate the potential of G-band radars for cloud and precipitation research. The field experiment, which coordinated an X-, Ka-, W- and G-band radar, revealed that the differential reflectivity from Ka–G band pair provides larger signals than the traditional Ka–W pairing underpinning an increased sensitivity to smaller amounts of liquid and ice water mass and sizes.
Tobias Sebastian Finn, Gernot Geppert, and Felix Ament
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-672, https://doi.org/10.5194/hess-2020-672, 2021
Revised manuscript not accepted
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Through the lens of recent developments in hydrological modelling and data assimilation, we hourly update the soil moisture with ensemble data assimilation and sparse 2-metre-temperature observations in a coupled limited area model system. In idealized experiments, we improve the soil moisture analysis by coupled data assimilation across the atmosphere-land interface. We conclude that we can merge the separated assimilation cycles for the atmosphere and land surface into one single cycle.
Marvin Heidkamp, Felix Ament, Philipp de Vrese, and Andreas Chlond
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-75, https://doi.org/10.5194/esd-2020-75, 2020
Publication in ESD not foreseen
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This study deals with leaf thermoregulation, a process that describes the ability of leaves to buffer against ambient temperatures. In the past, this effect has been investigated at the leaf scale, but not on the canopy or global scale. Here we try to close this scientific gap by studying the large-scale effect of leaf thermoregulation using the Max Planck Institute's Earth system model. We believe that our study provides valuable insights for modelers and observers.
Sonja Drueke, Daniel J. Kirshbaum, and Pavlos Kollias
Atmos. Chem. Phys., 20, 13217–13239, https://doi.org/10.5194/acp-20-13217-2020, https://doi.org/10.5194/acp-20-13217-2020, 2020
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This numerical study provides insights into selected environmental sensitivities of shallow-cumulus dilution. Among the parameters under consideration, the dilution of the cloud cores is strongly sensitive to continentality and cloud-layer relative humidity and weakly sensitive to subcloud- and cloud-layer depths. The impacts of all four parameters are interpreted using a similarity theory of shallow cumulus and buoyancy-sorting arguments.
Alessandro Battaglia, Pavlos Kollias, Ranvir Dhillon, Katia Lamer, Marat Khairoutdinov, and Daniel Watters
Atmos. Meas. Tech., 13, 4865–4883, https://doi.org/10.5194/amt-13-4865-2020, https://doi.org/10.5194/amt-13-4865-2020, 2020
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Warm rain accounts for slightly more than 30 % of the total rain amount and 70 % of the total rain area in the tropical belt and usually appears in kilometer-size cells. Spaceborne radars adopting millimeter wavelengths are excellent tools for detecting such precipitation types and for separating between the cloud and rain components. Our work highlights the benefits of operating multifrequency radars and discusses the impact of antenna footprints in quantitative estimates of liquid water paths.
Mario Mech, Maximilian Maahn, Stefan Kneifel, Davide Ori, Emiliano Orlandi, Pavlos Kollias, Vera Schemann, and Susanne Crewell
Geosci. Model Dev., 13, 4229–4251, https://doi.org/10.5194/gmd-13-4229-2020, https://doi.org/10.5194/gmd-13-4229-2020, 2020
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The Passive and Active Microwave TRAnsfer tool (PAMTRA) is a public domain software package written in Python and Fortran for the simulation of microwave remote sensing observations. PAMTRA models the interaction of radiation with gases, clouds, precipitation, and the surface using either in situ observations or model output as input parameters. The wide range of applications is demonstrated for passive (radiometer) and active (radar) instruments on ground, airborne, and satellite platforms.
Katia Lamer, Pavlos Kollias, Alessandro Battaglia, and Simon Preval
Atmos. Meas. Tech., 13, 2363–2379, https://doi.org/10.5194/amt-13-2363-2020, https://doi.org/10.5194/amt-13-2363-2020, 2020
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According to ground-based radar observations, 50 % of liquid low-level clouds over the Atlantic extend below 1.2 km and are thinner than 400 m, thus limiting their detection from space. Using an emulator, we estimate that a 250 m resolution radar would capture cloud base better than the CloudSat radar which misses about 52 %. The more sensitive EarthCARE radar is expected to capture cloud cover but stretch cloud. This calls for the operation of interlaced pulse modes for future space missions.
Montserrat Costa-Surós, Odran Sourdeval, Claudia Acquistapace, Holger Baars, Cintia Carbajal Henken, Christa Genz, Jonas Hesemann, Cristofer Jimenez, Marcel König, Jan Kretzschmar, Nils Madenach, Catrin I. Meyer, Roland Schrödner, Patric Seifert, Fabian Senf, Matthias Brueck, Guido Cioni, Jan Frederik Engels, Kerstin Fieg, Ksenia Gorges, Rieke Heinze, Pavan Kumar Siligam, Ulrike Burkhardt, Susanne Crewell, Corinna Hoose, Axel Seifert, Ina Tegen, and Johannes Quaas
Atmos. Chem. Phys., 20, 5657–5678, https://doi.org/10.5194/acp-20-5657-2020, https://doi.org/10.5194/acp-20-5657-2020, 2020
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The impact of anthropogenic aerosols on clouds is a key uncertainty in climate change. This study analyses large-domain simulations with a new high-resolution model to investigate the differences in clouds between 1985 and 2013 comparing multiple observational datasets. The differences in aerosol and in cloud droplet concentrations are clearly detectable. For other quantities, the detection and attribution proved difficult, despite a substantial impact on the Earth's energy budget.
Elena Ruiz-Donoso, André Ehrlich, Michael Schäfer, Evelyn Jäkel, Vera Schemann, Susanne Crewell, Mario Mech, Birte Solveig Kulla, Leif-Leonard Kliesch, Roland Neuber, and Manfred Wendisch
Atmos. Chem. Phys., 20, 5487–5511, https://doi.org/10.5194/acp-20-5487-2020, https://doi.org/10.5194/acp-20-5487-2020, 2020
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Mixed-phase clouds, formed of water droplets and ice crystals, appear frequently in Arctic regions. Characterizing the distribution of liquid water and ice inside the cloud appropriately is important because it influences the cloud's impact on the surface temperature. In this study, we combined images of the cloud top with measurements inside the cloud to analyze in detail the 3D spatial distribution of liquid and ice in two mixed-phase clouds occurring under different meteorological scenarios.
Mariko Oue, Aleksandra Tatarevic, Pavlos Kollias, Dié Wang, Kwangmin Yu, and Andrew M. Vogelmann
Geosci. Model Dev., 13, 1975–1998, https://doi.org/10.5194/gmd-13-1975-2020, https://doi.org/10.5194/gmd-13-1975-2020, 2020
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We developed the Cloud-resolving model Radar SIMulator (CR-SIM) capable of apples-to-apples comparisons between the multiwavelength, zenith-pointing, and scanning radar and multi-remote-sensing (radar and lidar) observations and the high-resolution atmospheric model output. Applications of CR-SIM as a virtual observatory operator aid interpretation of the differences and improve understanding of the representativeness errors due to the sampling limitations of the ground-based measurements.
Tobias Marke, Ulrich Löhnert, Vera Schemann, Jan H. Schween, and Susanne Crewell
Atmos. Chem. Phys., 20, 1723–1736, https://doi.org/10.5194/acp-20-1723-2020, https://doi.org/10.5194/acp-20-1723-2020, 2020
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In this study, land surface and atmosphere interactions are addressed using ground-based remote sensing, satellite products, and high-resolution large-eddy simulations. The focus is on water vapor transport from the surface into the atmosphere. Patterns found in long-term observations can be linked to properties of the surrounding land surface. The simulation results suggest that a different distribution of land use types has implications for boundary layer characteristics and clouds.
Vera Schemann and Kerstin Ebell
Atmos. Chem. Phys., 20, 475–485, https://doi.org/10.5194/acp-20-475-2020, https://doi.org/10.5194/acp-20-475-2020, 2020
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In this study, we apply a high-resolution model at the observation supersite Ny-Ålesund (Svalbard) to evaluate mixed-phase clouds. These clouds are a potential driver for the stronger warming in the Arctic compared to the global mean, but their representation in climate models is typically rather poor due to complex microphysical processes. The presented combination of high-resolution modeling and long-term state-of-the-art observations can lead to improved process understanding.
Fan Yang, Robert McGraw, Edward P. Luke, Damao Zhang, Pavlos Kollias, and Andrew M. Vogelmann
Atmos. Meas. Tech., 12, 5817–5828, https://doi.org/10.5194/amt-12-5817-2019, https://doi.org/10.5194/amt-12-5817-2019, 2019
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In-cloud supersaturation is crucial for droplet activation, growth, and drizzle initiation but is poorly known and hardly measured. Here we provide a novel method to estimate supersaturation fluctuation in stratocumulus clouds using remote-sensing measurements, and results show that our estimated supersaturation agrees reasonably well with in situ measurements. Our method provides a unique way to estimate supersaturation in stratocumulus clouds from long-term ground-based observations.
Mario Mech, Leif-Leonard Kliesch, Andreas Anhäuser, Thomas Rose, Pavlos Kollias, and Susanne Crewell
Atmos. Meas. Tech., 12, 5019–5037, https://doi.org/10.5194/amt-12-5019-2019, https://doi.org/10.5194/amt-12-5019-2019, 2019
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An improved understanding of Arctic mixed-phase clouds and their contribution to Arctic warming can be achieved by observations from airborne platforms with remote sensing instruments. Such an instrument is MiRAC combining active and passive techniques to gain information on the distribution of clouds, the occurrence of precipitation, and the amount of liquid and ice within the cloud. Operated during a campaign in Arctic summer, it could observe lower clouds often not seen by spaceborne radars.
Pavlos Kollias, Bernat Puigdomènech Treserras, and Alain Protat
Atmos. Meas. Tech., 12, 4949–4964, https://doi.org/10.5194/amt-12-4949-2019, https://doi.org/10.5194/amt-12-4949-2019, 2019
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Profiling millimeter-wavelength radars are the cornerstone instrument of surface-based observatories. Calibrating these radars is important for establishing a long record of observations suitable for model evaluation and improvement. Here, the CloudSat CPR is used to assess the calibration of a record over 10 years long of ARM cloud radar observations (a total of 44 years). The results indicate that correction coefficients are needed to improve record reliability and usability.
Katia Lamer, Bernat Puigdomènech Treserras, Zeen Zhu, Bradley Isom, Nitin Bharadwaj, and Pavlos Kollias
Atmos. Meas. Tech., 12, 4931–4947, https://doi.org/10.5194/amt-12-4931-2019, https://doi.org/10.5194/amt-12-4931-2019, 2019
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This article describes the three newly deployed second-generation radar of the Atmospheric Radiation Measurement program. Techniques to retrieve precipitation rate from their measurements are presented: noise and clutter filtering, gas and liquid attenuation correction, and radar reflectivity calibration. Rain rate for a 40 km radius domain around Graciosa estimated from all three radar differ, which highlights the need to consider sensor capabilities when interpreting radar measurements.
Helge Knoop, Felix Ament, and Björn Maronga
Adv. Sci. Res., 16, 143–148, https://doi.org/10.5194/asr-16-143-2019, https://doi.org/10.5194/asr-16-143-2019, 2019
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This paper proposes a new generic method to define and detect wind gusts from high-resolution wind velocity data. The method describes any specific gust by an amplitude and period and allows the detection of individual gusts in time using wavelet-analysis. The result of a full gust analysis using this method yields a so-called characteristic gust distribution for the respective wind velocity data, which can serve as a direct link to the physical impact a particular gust has on e.g. an aircraft.
Heike Konow, Marek Jacob, Felix Ament, Susanne Crewell, Florian Ewald, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Mario Mech, and Bjorn Stevens
Earth Syst. Sci. Data, 11, 921–934, https://doi.org/10.5194/essd-11-921-2019, https://doi.org/10.5194/essd-11-921-2019, 2019
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High-resolution measurements of maritime clouds are relatively scarce. Airborne cloud radar, microwave radiometer and dropsonde observations are used to expand these data. The measurements are unified into one data set to enable easy joint analyses of several or all instruments together to gain insight into cloud properties and atmospheric state. The data set contains measurements from four campaigns between December 2013 and October 2016 over the tropical and midlatitude Atlantic.
Alessandro Battaglia and Pavlos Kollias
Atmos. Meas. Tech., 12, 3335–3349, https://doi.org/10.5194/amt-12-3335-2019, https://doi.org/10.5194/amt-12-3335-2019, 2019
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This work investigates the potential of an innovative differential absorption radar for retrieving relative humidity inside ice clouds. The radar exploits the strong spectral dependence of the water vapour absorption for frequencies close to the 183 GHz water vapour band.
Results show that observations from a system with 4–6 frequencies can provide
novel information for understanding the formation and growth of ice crystals.
Marek Jacob, Felix Ament, Manuel Gutleben, Heike Konow, Mario Mech, Martin Wirth, and Susanne Crewell
Atmos. Meas. Tech., 12, 3237–3254, https://doi.org/10.5194/amt-12-3237-2019, https://doi.org/10.5194/amt-12-3237-2019, 2019
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Tropical clouds are a key climate component but are still not fully understood. Therefore, we analyze airborne remote sensing measurements that were taken in the dry and wet seasons over the Atlantic east of Barbados. From these we derive sub-kilometer resolution data of vertically integrated atmospheric water vapor and liquid water. Results show that although the humidity is lower in the dry season, clouds are more frequent, contain more water, and produce more rain than in the wet season.
Mariko Oue, Pavlos Kollias, Alan Shapiro, Aleksandra Tatarevic, and Toshihisa Matsui
Atmos. Meas. Tech., 12, 1999–2018, https://doi.org/10.5194/amt-12-1999-2019, https://doi.org/10.5194/amt-12-1999-2019, 2019
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This study investigated impacts of the selected radar volume coverage pattern, the sampling time period, the number of radars used, and the added value of advection correction on the retrieval of vertical air motion from a multi-Doppler-radar technique. The results suggest that the use of rapid-scan radars can substantially improve the quality of wind retrievals and that the retrieved wind field needs to be carefully used considering the limitations of the radar observing system.
Christoph Böhm, Odran Sourdeval, Johannes Mülmenstädt, Johannes Quaas, and Susanne Crewell
Atmos. Meas. Tech., 12, 1841–1860, https://doi.org/10.5194/amt-12-1841-2019, https://doi.org/10.5194/amt-12-1841-2019, 2019
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The cloud base height (CBH) is important for air traffic, for describing the energy budget of the Earth and for other applications. Ground-based CBH measurements are only available for individual sites and mostly limited to land. Satellites are a powerful tool for global coverage. While the cloud top height is derived operationally, the derivation of CBH from space is more difficult as the clouds hide their base. Here, we present a method to retrieve the CBH from multi-angle satellite data.
Kevin Wolf, André Ehrlich, Marek Jacob, Susanne Crewell, Martin Wirth, and Manfred Wendisch
Atmos. Meas. Tech., 12, 1635–1658, https://doi.org/10.5194/amt-12-1635-2019, https://doi.org/10.5194/amt-12-1635-2019, 2019
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Using passive spectral solar radiation and active lidar, radar, and microwave measurements with HALO during NARVAL-II, the cloud droplet number concentration of shallow trade wind cumulus is estimated. With stepwise inclusion of the different instruments into the retrieval, the benefits of the synergetic approach based on artificial measurements and two cloud cases are demonstrated. Significant improvement with the synergetic method compared to the solar-radiation-only method is reported.
Erlend M. Knudsen, Bernd Heinold, Sandro Dahlke, Heiko Bozem, Susanne Crewell, Irina V. Gorodetskaya, Georg Heygster, Daniel Kunkel, Marion Maturilli, Mario Mech, Carolina Viceto, Annette Rinke, Holger Schmithüsen, André Ehrlich, Andreas Macke, Christof Lüpkes, and Manfred Wendisch
Atmos. Chem. Phys., 18, 17995–18022, https://doi.org/10.5194/acp-18-17995-2018, https://doi.org/10.5194/acp-18-17995-2018, 2018
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The paper describes the synoptic development during the ACLOUD/PASCAL airborne and ship-based field campaign near Svalbard in spring 2017. This development is presented using near-surface and upperair meteorological observations, satellite, and model data. We first present time series of these data, from which we identify and characterize three key periods. Finally, we put our observations in historical and regional contexts and compare our findings to other Arctic field campaigns.
Guangjie Zheng, Yang Wang, Allison C. Aiken, Francesca Gallo, Michael P. Jensen, Pavlos Kollias, Chongai Kuang, Edward Luke, Stephen Springston, Janek Uin, Robert Wood, and Jian Wang
Atmos. Chem. Phys., 18, 17615–17635, https://doi.org/10.5194/acp-18-17615-2018, https://doi.org/10.5194/acp-18-17615-2018, 2018
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Here, we elucidate the key processes that drive marine boundary layer (MBL) aerosol size distribution in the eastern North Atlantic (ENA) using long-term measurements. The governing equations of particle concentration are established for different modes. Particles entrained from the free troposphere represent the major source of MBL cloud condensation nuclei (CCN), contributing both directly to CCN population and indirectly by supplying Aitken-mode particles that grow to CCN in the MBL.
Akio Hansen, Felix Ament, Verena Grützun, and Andrea Lammert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-259, https://doi.org/10.5194/gmd-2018-259, 2018
Publication in GMD not foreseen
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Clouds are responsible for large uncertainties in atmospheric models, whereby the evaluation is very challenging due to their complexity. The Cloudnet project uses multi-sensor observations to create a comprehensive Target Classification showing the cloud structure and phase, but there is no comparable model output available. The presented cloud classification algorithm generates a consistent product, which provides a comprehensive view on clouds and is used for further in-depth evaluation.
Katia Lamer, Ann M. Fridlind, Andrew S. Ackerman, Pavlos Kollias, Eugene E. Clothiaux, and Maxwell Kelley
Geosci. Model Dev., 11, 4195–4214, https://doi.org/10.5194/gmd-11-4195-2018, https://doi.org/10.5194/gmd-11-4195-2018, 2018
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Weather and climate predictions of cloud, rain, and snow occurrence remain uncertain, in part because guidance from observation is incomplete. We present a tool that transforms predictions into observations from ground-based remote sensors. Liquid water and ice occurrence errors associated with the transformation are below 8 %, with ~ 3 % uncertainty. This (GO)2-SIM forward-simulator tool enables better evaluation of cloud, rain, and snow occurrence predictions using available observations.
Marvin Heidkamp, Andreas Chlond, and Felix Ament
Geosci. Model Dev., 11, 3465–3479, https://doi.org/10.5194/gmd-11-3465-2018, https://doi.org/10.5194/gmd-11-3465-2018, 2018
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The core of every climate model is the solution of the surface energy balance. Numerical approaches are mandatory to calculate the land's response to solar input. However, different numerical approaches should not affect the physical results. Here we develop a physical approach that determines how the available energy is divided into radiative and heat fluxes. A key element of this scheme is the inclusion of different types of heat storages in the canopy layer.
Fan Yang, Pavlos Kollias, Raymond A. Shaw, and Andrew M. Vogelmann
Atmos. Chem. Phys., 18, 7313–7328, https://doi.org/10.5194/acp-18-7313-2018, https://doi.org/10.5194/acp-18-7313-2018, 2018
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Cloud droplet size distribution (CDSD), which is related to cloud albedo and lifetime, is usually observed broader than predicted from adiabatic parcel calculations. Results in this study show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation. Our results suggest that it is important to consider both curvature and solute effects before and after cloud droplet activation in a 3-D cloud model.
Olga Henneberg, Felix Ament, and Verena Grützun
Atmos. Chem. Phys., 18, 6413–6425, https://doi.org/10.5194/acp-18-6413-2018, https://doi.org/10.5194/acp-18-6413-2018, 2018
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Soil moisture influences the occurrence of convective precipitation. An accurate knowledge of soil moisture might improve the prediction of convective cells.
But the model uncertainty overshadows the impact of soil moisture in convection resolving models. Only drastic soil moisture changes can exhibit the model uncertainties. Both the enhanced and reduced soil moisture result in a reduced precipitation rate. We point out the need for uncertainty estimations in soil moisture studies.
Damao Zhang, Zhien Wang, Pavlos Kollias, Andrew M. Vogelmann, Kang Yang, and Tao Luo
Atmos. Chem. Phys., 18, 4317–4327, https://doi.org/10.5194/acp-18-4317-2018, https://doi.org/10.5194/acp-18-4317-2018, 2018
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Ice production in atmospheric clouds is important for global water cycle and radiation budget. Active satellite remote sensing measurements are analyzed to quantitatively study primary ice particle production in stratiform mixed-phase clouds on a global scale. We quantify the geographic and seasonal variations of ice production and their correlations with aerosol, especially mineral dust activities. The results can be used to evaluate mixed-phased clouds simulations by global climate models.
Xiaoli Zhou, Andrew S. Ackerman, Ann M. Fridlind, Robert Wood, and Pavlos Kollias
Atmos. Chem. Phys., 17, 12725–12742, https://doi.org/10.5194/acp-17-12725-2017, https://doi.org/10.5194/acp-17-12725-2017, 2017
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Shallow maritime clouds make a well-known transition from stratocumulus to trade cumulus with flow from the subtropics equatorward. Three-day large-eddy simulations that investigate the potential influence of overlying African biomass burning plumes during that transition indicate that cloud-related impacts are likely substantially cooling to negligible at the top of the atmosphere, with magnitude sensitive to background and perturbation aerosol and cloud properties.
Kirk W. North, Mariko Oue, Pavlos Kollias, Scott E. Giangrande, Scott M. Collis, and Corey K. Potvin
Atmos. Meas. Tech., 10, 2785–2806, https://doi.org/10.5194/amt-10-2785-2017, https://doi.org/10.5194/amt-10-2785-2017, 2017
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Vertical air motion retrievals from 3DVAR multiple distributed scanning Doppler radars are compared against collocated profiling radars and retrieved from an upward iteration integration iterative technique to characterize their veracity. The retrieved vertical air motions are generally within 1–2 m s−1 of agreement with profiling radars and better solution than the upward integration technique, and therefore can be used as a means to improve parameterizations in numerical models moving forward.
Claudia Acquistapace, Stefan Kneifel, Ulrich Löhnert, Pavlos Kollias, Maximilian Maahn, and Matthias Bauer-Pfundstein
Atmos. Meas. Tech., 10, 1783–1802, https://doi.org/10.5194/amt-10-1783-2017, https://doi.org/10.5194/amt-10-1783-2017, 2017
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The goal of the paper is to understand what the optimal cloud radar settings for drizzle detection are. The number of cloud radars in the world has increased in the last 10 years and it is important to develop strategies to derive optimal settings which can be applied to all radar systems. The study is part of broader research focused on better understanding the microphysical process of drizzle growth using ground-based observations.
Andreas Macke, Patric Seifert, Holger Baars, Christian Barthlott, Christoph Beekmans, Andreas Behrendt, Birger Bohn, Matthias Brueck, Johannes Bühl, Susanne Crewell, Thomas Damian, Hartwig Deneke, Sebastian Düsing, Andreas Foth, Paolo Di Girolamo, Eva Hammann, Rieke Heinze, Anne Hirsikko, John Kalisch, Norbert Kalthoff, Stefan Kinne, Martin Kohler, Ulrich Löhnert, Bomidi Lakshmi Madhavan, Vera Maurer, Shravan Kumar Muppa, Jan Schween, Ilya Serikov, Holger Siebert, Clemens Simmer, Florian Späth, Sandra Steinke, Katja Träumner, Silke Trömel, Birgit Wehner, Andreas Wieser, Volker Wulfmeyer, and Xinxin Xie
Atmos. Chem. Phys., 17, 4887–4914, https://doi.org/10.5194/acp-17-4887-2017, https://doi.org/10.5194/acp-17-4887-2017, 2017
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This article provides an overview of the instrumental setup and the main results obtained during the two HD(CP)2 Observational Prototype Experiments HOPE-Jülich and HOPE-Melpitz conducted in Germany in April–May and Sept 2013, respectively. Goal of the field experiments was to provide high-resolution observational datasets for both, improving the understaning of boundary layer and cloud processes, as well as for the evaluation of the new ICON model that is run at 156 m horizontal resolution.
Bernd Schalge, Jehan Rihani, Gabriele Baroni, Daniel Erdal, Gernot Geppert, Vincent Haefliger, Barbara Haese, Pablo Saavedra, Insa Neuweiler, Harrie-Jan Hendricks Franssen, Felix Ament, Sabine Attinger, Olaf A. Cirpka, Stefan Kollet, Harald Kunstmann, Harry Vereecken, and Clemens Simmer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-557, https://doi.org/10.5194/hess-2016-557, 2016
Manuscript not accepted for further review
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In this work we show how we used a coupled atmosphere-land surface-subsurface model at highest possible resolution to create a testbed for data assimilation. The model was able to capture all important processes and interactions between the compartments as well as showing realistic statistical behavior. This proves that using a model as a virtual truth is possible and it will enable us to develop data assimilation methods where states and parameters are updated across compartment.
María Barrera-Verdejo, Susanne Crewell, Ulrich Löhnert, Emiliano Orlandi, and Paolo Di Girolamo
Atmos. Meas. Tech., 9, 4013–4028, https://doi.org/10.5194/amt-9-4013-2016, https://doi.org/10.5194/amt-9-4013-2016, 2016
Alexander Lemburg, Martin Claussen, and Felix Ament
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-68, https://doi.org/10.5194/cp-2016-68, 2016
Manuscript not accepted for further review
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The deforestation of Easter Island several hundred years ago might have influenced its local near-surface climate. With a series of numerical model experiments we investigate the impact of deforestation on precipitation and near-surface climate. We find that a deforested Easter Island appears to be significantly less resistant to drought than a forested island and thus, deforestation has probably exacerbated the effects of past climate drought spells on Easter Island's socio-ecological systems.
A. Lammert and F. Ament
Earth Syst. Sci. Data, 7, 311–317, https://doi.org/10.5194/essd-7-311-2015, https://doi.org/10.5194/essd-7-311-2015, 2015
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The paper presents long-term measurements of turbulent fluxes at the research platform FINO2 in the Baltic Sea. The platform was equipped at two heights (6.8 and 13.8m) for the observation of wind, temperature, humidity and CO2 over a time period of 1.5 years. The paper shows the measured quantities as well as the turbulent fluxes, latent and sensible heat, momentum and CO2 flux. In contrast to the constant-flux layer approach, we found differences in the CO2 fluxes between 6.8 and 13.8m.
C. Merker, G. Peters, M. Clemens, K. Lengfeld, and F. Ament
Atmos. Meas. Tech., 8, 2521–2530, https://doi.org/10.5194/amt-8-2521-2015, https://doi.org/10.5194/amt-8-2521-2015, 2015
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The theory of an approach for absolute radar calibration with respect to reflectivity and without a previously calibrated reference device is laid out and validated. The method requires a network of two horizontally oriented radars operating within a frequency range strongly attenuated by liquid water and a radar allowing for drop size distribution measurements with height (e.g. micro rain radar). The analysis by means of synthetic data shows potential for future practical application.
M. Barrera-Verdejo, S. Crewell, U. Löhnert, E. Orlandi, and P. Di Girolamo
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-8-5467-2015, https://doi.org/10.5194/amtd-8-5467-2015, 2015
Revised manuscript not accepted
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
I. V. Gorodetskaya, S. Kneifel, M. Maahn, K. Van Tricht, W. Thiery, J. H. Schween, A. Mangold, S. Crewell, and N. P. M. Van Lipzig
The Cryosphere, 9, 285–304, https://doi.org/10.5194/tc-9-285-2015, https://doi.org/10.5194/tc-9-285-2015, 2015
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Our paper presents a new cloud-precipitation-meteorological observatory established in the escarpment zone of Dronning Maud Land, East Antarctica. The site is characterised by bimodal cloud occurrence (clear sky or overcast) with liquid-containing clouds occurring 20% of the cloudy periods. Local surface mass balance strongly depends on rare intense snowfall events. A substantial part of the accumulated snow is removed by surface and drifting snow sublimation and wind-driven snow erosion.
M. Mech, E. Orlandi, S. Crewell, F. Ament, L. Hirsch, M. Hagen, G. Peters, and B. Stevens
Atmos. Meas. Tech., 7, 4539–4553, https://doi.org/10.5194/amt-7-4539-2014, https://doi.org/10.5194/amt-7-4539-2014, 2014
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Here the High Altitude and LOng range research aircraft Microwave Package (HAMP) is introduced. The package consists
of three passive radiometer modules with 26 channels between 22
and 183 GHz and a 36 GHz Doppler cloud radar. The manuscript
describes the instrument specifications, the installation in the aircraft, and the operation. Furthermore, results from simulation
and retrieval studies, as well as measurements from a first test
campaign, are shown.
K. Lengfeld, M. Clemens, H. Münster, and F. Ament
Atmos. Meas. Tech., 7, 4151–4166, https://doi.org/10.5194/amt-7-4151-2014, https://doi.org/10.5194/amt-7-4151-2014, 2014
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This publication intends to prove that a network of low-cost local area weather radars with a time resolution of 30s and range resolution of 60m is a reliable and scientifically valuable comple-ment to nationwide radar networks, especially in urban areas. The advantages of high temporal resolution and multiple coverage in overlapping areas are proven to enhance the quality of pre-cipitation estimates. Long-term comparison with C-band radar confirms very good accordance with POD>90% and FAR<10%.
J. H. Schween, A. Hirsikko, U. Löhnert, and S. Crewell
Atmos. Meas. Tech., 7, 3685–3704, https://doi.org/10.5194/amt-7-3685-2014, https://doi.org/10.5194/amt-7-3685-2014, 2014
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Two different methods for the determination of the mixing layer height (MLH) are investigated with a one-year data set from central Europe: (i) based on a significant gradient of backscatter and (ii) on the vertical velocity. The aerosol-based method shows significant over-estimation in the morning hours when the ML grows into the residual layer and late afternoon hours when turbulent mixing decays. This results in systematic over-estimation of average characteristcs as e.g. maximum MLH.
G. Maschwitz, U. Löhnert, S. Crewell, T. Rose, and D. D. Turner
Atmos. Meas. Tech., 6, 2641–2658, https://doi.org/10.5194/amt-6-2641-2013, https://doi.org/10.5194/amt-6-2641-2013, 2013
V. Meunier, U. Löhnert, P. Kollias, and S. Crewell
Atmos. Meas. Tech., 6, 1171–1187, https://doi.org/10.5194/amt-6-1171-2013, https://doi.org/10.5194/amt-6-1171-2013, 2013
A. Tetzlaff, L. Kaleschke, C. Lüpkes, F. Ament, and T. Vihma
The Cryosphere, 7, 153–166, https://doi.org/10.5194/tc-7-153-2013, https://doi.org/10.5194/tc-7-153-2013, 2013
Related subject area
Atmospheric sciences
Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description and preliminary experimental results
Optimized dynamic mode decomposition for reconstruction and forecasting of atmospheric chemistry data
Interpolating turbulent heat fluxes missing from a prairie observation on the Tibetan Plateau using artificial intelligence models
Carbon dioxide plume dispersion simulated at the hectometer scale using DALES: model formulation and observational evaluation
Low-level jets in the North and Baltic seas: mesoscale model sensitivity and climatology using WRF V4.2.1
SynRad v1.0: a radar forward operator to simulate synthetic weather radar observations from volcanic ash clouds
Chempath 1.0: an open-source pathway analysis program for photochemical models
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Atmospheric moisture tracking with WAM2layers v3
A new set of indicators for model evaluation complementing FAIRMODE's modelling quality objective (MQO)
Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
The Atmospheric Potential Oxygen forward Model Intercomparison Project (APO-MIP1): Evaluating simulated atmospheric transport of air-sea gas exchange tracers and APO flux products
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Development of a High-Resolution Coupled SHiELD-MOM6 Model. Part I – Model Overview, Coupling Technique, and Validation in a Regional Setup
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
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A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
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Yongzhu Liu, Xiaoye Zhang, Wei Han, Chao Wang, Wenxing Jia, Deying Wang, Zhaorong Zhuang, and Xueshun Shen
Geosci. Model Dev., 18, 4855–4876, https://doi.org/10.5194/gmd-18-4855-2025, https://doi.org/10.5194/gmd-18-4855-2025, 2025
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In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts, we developed a strongly coupled aerosol–meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, based on the framework of the incremental analysis scheme of the China Meteorological Administration Global Forecasting System (CMA-GFS) operational global numerical weather model. The results show that assimilating BC (black carbon) observations can generate analysis increments not only for BC but also for atmospheric variables.
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev., 18, 4667–4684, https://doi.org/10.5194/gmd-18-4667-2025, https://doi.org/10.5194/gmd-18-4667-2025, 2025
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We develop the data-driven method of dynamic mode decomposition for producing a robust and stable surrogate reduced-order model of atmospheric chemistry dynamics. The model is computationally efficient, provides interpretable patterns of activity, and produces uncertainty quantification metrics. It is ideal for the forecasting of atmospheric chemistry in a computationally tractable manner.
Quanzhe Hou, Zhiqiu Gao, Zexia Duan, and Minghui Yu
Geosci. Model Dev., 18, 4625–4641, https://doi.org/10.5194/gmd-18-4625-2025, https://doi.org/10.5194/gmd-18-4625-2025, 2025
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This study evaluates various machine learning and statistical methods for interpolating turbulent heat flux data over the Tibetan Plateau. The Transformer model showed the best performance, leading to the development of the Transformer_CNN model, which combines global and local attention mechanisms. Results show that Transformer_CNN outperforms the other models and was successfully applied to interpolate heat flux data from 2007 to 2016.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart J. H. van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
Geosci. Model Dev., 18, 4571–4599, https://doi.org/10.5194/gmd-18-4571-2025, https://doi.org/10.5194/gmd-18-4571-2025, 2025
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We introduce a new simulation platform based on the Dutch Atmospheric Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in turbulent environments at a hectometer resolution. This model incorporates both anthropogenic emission inventories and online ecosystem fluxes. Simulation results for the main urban area in the Netherlands demonstrate the strong potential of DALES to improve CO2 emission modeling and to support mitigation strategies.
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
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Low-level jets (LLJs) are strong winds in the lower atmosphere that are important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025, https://doi.org/10.5194/gmd-18-4417-2025, 2025
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A numerical model that simulates the measurement processes behind the ground-based radars used to detect volcanic ash clouds is introduced. Using weather radars to detect volcanic clouds is not ideal, as fine ash particles are smaller than raindrops and remain undetected. We evaluate the performance of weather radars to study ash clouds and to identify optimal frequencies that balance the trade-off between a higher return signal and the higher path attenuation that comes at these higher frequencies.
Daniel Garduno Ruiz, Colin Goldblatt, and Anne-Sofie Ahm
Geosci. Model Dev., 18, 4433–4454, https://doi.org/10.5194/gmd-18-4433-2025, https://doi.org/10.5194/gmd-18-4433-2025, 2025
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Photochemical models describe how the composition of the atmosphere changes due to chemical reactions, transport, and other processes. These models are useful for studying the composition of the Earth's and other planets' atmospheres. Understanding the results of these models can be difficult. Here, we build on previous work to develop open-source code that can identify the reaction chains (pathways) that produce the results of these models, facilitating the understanding of these results.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
Geosci. Model Dev., 18, 4353–4398, https://doi.org/10.5194/gmd-18-4353-2025, https://doi.org/10.5194/gmd-18-4353-2025, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line And Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, this model is valuable for airglow research and astronomical observatories.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
Geosci. Model Dev., 18, 4335–4352, https://doi.org/10.5194/gmd-18-4335-2025, https://doi.org/10.5194/gmd-18-4335-2025, 2025
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We introduce a new version of WAM2layers (Water Accounting Model – 2 layers), a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data had become a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent, reliable, and easier to maintain.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
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We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and winter–summer gradients reveal issues. O3 evaluation shows that seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Yuming Jin, Britton B. Stephens, Matthew C. Long, Naveen Chandra, Frédéric Chevallier, Joram J. D. Hooghiem, Ingrid T. Luijkx, Shamil Maksyutov, Eric J. Morgan, Yosuke Niwa, Prabir K. Patra, Christian Rödenbeck, and Jesse Vance
EGUsphere, https://doi.org/10.5194/egusphere-2025-1736, https://doi.org/10.5194/egusphere-2025-1736, 2025
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We carry out a comprehensive atmospheric transport model (ATM) intercomparison project. This project aims to evaluate errors in ATMs and three air-sea O2 exchange products by comparing model simulations with observations collected from surface stations, ships, and aircraft. We also present a model evaluation framework to independently quantify transport-related and flux-related biases that contribute to model-observation discrepancies in atmospheric tracer distributions.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1690, https://doi.org/10.5194/egusphere-2025-1690, 2025
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We introduce a new high-resolution model that couple the atmosphere and ocean to better simulate extreme weather events. It combines GFDL’s advanced atmospheric and ocean models with a powerful coupling system that allows robust and efficient two-way interactions. Simulations show the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model is a key step toward improving extreme weather forecast.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Cited articles
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M.,
and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction
with the COSMO Model: Description and Sensitivities, Mon. Weather Rev.,
139, 3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011. a
Bodas-Salcedo, A., Webb, M., Bony, S., Chepfer, H., Dufresne, J.-L., Klein, S.,
Zhang, Y., Marchand, R., Haynes, J., Pincus, R., and John, V. O.: COSP: Satellite
simulation software for model assessment, B. Am.
Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011. a
Bony, S. and Dufresne, J.-L.: Marine boundary layer clouds at the heart of
tropical cloud feedback uncertainties in climate models, Geophys. Res.
Lett., 32, L20806, https://doi.org/10.1029/2005GL023851, 2005. a
Bony, S., Stevens, B., Ament, F., Bigorre, S., Chazette, P., Crewell, S.,
Delanoë, J., Emanuel, K., Farrell, D., Flamant, C., Gross, S., Hirsch, L.,
Karstensen, J., Mayer, B., Nuijens, L., Ruppert, J. H., Sandu, I., Siebesma,
P., Speich, S., Szczap, F., Totems, J., Vogel, R., Wendisch, M., and Wirth,
M.: EUREC4A: A Field Campaign to Elucidate the Couplings
Between Clouds, Convection and Circulation, Surv. Geophys.,
38, 1529–1568, https://doi.org/10.1007/s10712-017-9428-0, 2017. a
Bretherton, C. S. and Blossey, P. N.: Understanding Mesoscale Aggregation of
Shallow Cumulus Convection Using Large-Eddy Simulation, J. Adv.
Model. Earth Sy., 9, 2798–2821, https://doi.org/10.1002/2017MS000981, 2017. a
Crewell, S., Ebell, K., Löhnert, U., and Turner, D. D.: Can liquid water
profiles be retrieved from passive microwave zenith observations?,
Geophys. Res. Lett., 36, L06803, https://doi.org/10.1029/2008GL036934, 2009. a
Dipankar, A., Stevens, B., Heinze, R., Moseley, C., Zängl, G., Giorgetta, M.,
and Brdar, S.: Large eddy simulation using the general circulation model
ICON, J. Adv. Model. Earth Sy., 7, 963–986,
https://doi.org/10.1002/2015MS000431, 2015. a
Ewald, F., Groß, S., Hagen, M., Hirsch, L., Delanoë, J., and Bauer-Pfundstein, M.: Calibration of a 35 GHz airborne cloud radar: lessons learned and intercomparisons with 94 GHz cloud radars, Atmos. Meas. Tech., 12, 1815–1839, https://doi.org/10.5194/amt-12-1815-2019, 2019. a, b
Frisch, A. S., Feingold, G., Fairall, C. W., Uttal, T., and Snider, J. B.: On
cloud radar and microwave radiometer measurements of stratus cloud liquid
water profiles, J. Geophys. Res.-Atmos., 103,
23195–23197, https://doi.org/10.1029/98JD01827, 1998. a
Genkova, I., Seiz, G., Zuidema, P., Zhao, G., and Di Girolamo, L.: Cloud top
height comparisons from ASTER, MISR, and MODIS for trade wind cumuli,
Remote Sens. Environ., 107, 211–222,
https://doi.org/10.1016/j.rse.2006.07.021, 2007. a, b, c
Grabowski, W. W., Morrison, H., Shima, S.-I., Abade, G. C., Dziekan, P., and
Pawlowska, H.: Modeling of Cloud Microphysics: Can We Do Better?,
B. Am. Meteorol. Soc., 100, 655–672,
https://doi.org/10.1175/BAMS-D-18-0005.1, 2019. a
Gutleben, M., Groß, S., and Wirth, M.: Cloud macro-physical properties in Saharan-dust-laden and dust-free North Atlantic trade wind regimes: a lidar case study, Atmos. Chem. Phys., 19, 10659–10673, https://doi.org/10.5194/acp-19-10659-2019, 2019. a, b
Heinze, R., Dipankar, A., Henken, C. C., Moseley, C., Sourdeval, O.,
Trömel, S., Xie, X., Adamidis, P., Ament, F., Baars, H., Barthlott, C.,
Behrendt, A., Blahak, U., Bley, S., Brdar, S., Brueck, M., Crewell, S.,
Deneke, H., Di Girolamo, P., Evaristo, R., Fischer, J., Frank, C.,
Friederichs, P., Göcke, T., Gorges, K., Hande, L., Hanke, M., Hansen, A.,
Hege, H.-C., Hoose, C., Jahns, T., Kalthoff, N., Klocke, D., Kneifel, S.,
Knippertz, P., Kuhn, A., van Laar, T., Macke, A., Maurer, V., Mayer, B.,
Meyer, C. I., Muppa, S. K., Neggers, R. A. J., Orlandi, E., Pantillon, F.,
Pospichal, B., Röber, N., Scheck, L., Seifert, A., Seifert, P., Senf, F.,
Siligam, P., Simmer, C., Steinke, S., Stevens, B., Wapler, K., Weniger, M.,
Wulfmeyer, V., Zängl, G., Zhang, D., and Quaas, J.: Large-eddy
simulations over Germany using ICON: a comprehensive evaluation, Q.
J. Roy. Meteor. Soc., 143, 69–100,
https://doi.org/10.1002/qj.2947, 2017. a
Jeevanjee, N. and Romps, D. M.: Convective self-aggregation, cold pools, and
domain size, Geophys. Res. Lett., 40, 994–998,
https://doi.org/10.1002/grl.50204, 2013. a
Khain, A. P., Beheng, K. D., Heymsfield, A., Korolev, A., Krichak, S. O.,
Levin, Z., Pinsky, M., Phillips, V., Prabhakaran, T., Teller, A., van der Heever, S.
C., and Yano, J.-I.: Representation of microphysical processes in
cloud-resolving models: Spectral (bin) microphysics versus bulk
parameterization, Rev. Geophys., 53, 247–322,
https://doi.org/10.1002/2014RG000468, 2015. a
Klingebiel, M., Ghate, V. P., Naumann, A. K., Ditas, F., Pöhlker, M. L.,
Pöhlker, C., Kandler, K., Konow, H., and Stevens, B.: Remote Sensing of
Sea Salt Aerosol below Trade Wind Clouds, J.
Atmos. Sci., 76, 1189–1202, https://doi.org/10.1175/JAS-D-18-0139.1, 2019. a
Klocke, D., Brück, M., Hohenegger, C., and Stevens, B.: Rediscovery of the
doldrums in storm-resolving simulations over the tropical Atlantic, Nat.
Geosci., 10, 891–896, https://doi.org/10.1038/s41561-017-0005-4, 2017. a, b, c, d
Konow, H., Jacob, M., Ament, F., Crewell, S., Ewald, F., Hagen, M., Hirsch, L., Jansen, F., Mech, M., and Stevens, B.: A unified data set of airborne cloud remote sensing using the HALO Microwave Package (HAMP), Earth Syst. Sci. Data, 11, 921–934, https://doi.org/10.5194/essd-11-921-2019, 2019. a, b
Krautstrunk, M. and Giez, A.: The Transition From FALCON to HALO Era
Airborne Atmospheric Research, in: Atmospheric Physics,
Springer Berlin Heidelberg, 609–624, https://doi.org/10.1007/978-3-642-30183-4_37, 2012. a
Küchler, N., Kneifel, S., Kollias, P., and Löhnert, U.: Revisiting Liquid
Water Content Retrievals in Warm Stratified Clouds: The
Modified Frisch, Geophys. Res. Lett., 45, 9323–9330,
https://doi.org/10.1029/2018GL079845, 2018. a
Lamer, K., Kollias, P., and Nuijens, L.: Observations of the variability of
shallow trade wind cumulus cloudiness and mass flux, J. Geophys.
Res.-Atmos., 120, 6161–6178, https://doi.org/10.1002/2014JD022950, 2015. a
Lamer, K., Fridlind, A. M., Ackerman, A. S., Kollias, P., Clothiaux, E. E., and Kelley, M.: (GO)2-SIM: a GCM-oriented ground-observation forward-simulator framework for objective evaluation of cloud and precipitation phase, Geosci. Model Dev., 11, 4195–4214, https://doi.org/10.5194/gmd-11-4195-2018, 2018. a, b, c
Leahy, L. V., Wood, R., Charlson, R. J., Hostetler, C. A., Rogers, R. R.,
Vaughan, M. A., and Winker, D. M.: On the nature and extent of optically thin
marine low clouds, J. Geophys. Res.-Atmos., 117, D22201,
https://doi.org/10.1029/2012JD017929, 2012. a, b, c, d
Mech, M., Orlandi, E., Crewell, S., Ament, F., Hirsch, L., Hagen, M., Peters, G., and Stevens, B.: HAMP – the microwave package on the High Altitude and LOng range research aircraft (HALO), Atmos. Meas. Tech., 7, 4539–4553, https://doi.org/10.5194/amt-7-4539-2014, 2014. a, b
Mech, M., Maahn, M., Kneifel, S., Ori, D., Orlandi, E., Kollias, P., Schemann, V., and Crewell, S.: PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere, Geosci. Model Dev., 13, 4229–4251, https://doi.org/10.5194/gmd-13-4229-2020, 2020. a, b
Medeiros, B., Nuijens, L., Antoniazzi, C., and Stevens, B.: Low-latitude
boundary layer clouds as seen by CALIPSO, J. Geophys. Res.-Atmos., 115, D23207, https://doi.org/10.1029/2010JD014437, 2010. a
Nuijens, L., Serikov, I., Hirsch, L., Lonitz, K., and Stevens, B.: The
distribution and variability of low-level cloud in the North Atlantic
trades, Q. J. Roy. Meteor. Soc., 140,
2364–2374, https://doi.org/10.1002/qj.2307, 2014. a, b
O, K.-T., Wood, R., and Tseng, H.-H.: Deeper, Precipitating PBLs Associated
With Optically Thin Veil Clouds in the Sc-Cu Transition, Geophys. Res.
Lett., 45, 5177–5184, https://doi.org/10.1029/2018GL077084, 2018. a, b, c
O’Connor, E. J., Hogan, R. J., and Illingworth, A. J.: Retrieving
Stratocumulus Drizzle Parameters Using Doppler Radar and Lidar,
J. Appl. Meteorol., 44, 14–27, https://doi.org/10.1175/JAM-2181.1, 2005. a
Oue, M., Tatarevic, A., Kollias, P., Wang, D., Yu, K., and Vogelmann, A. M.: The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory, Geosci. Model Dev., 13, 1975–1998, https://doi.org/10.5194/gmd-13-1975-2020, 2020. a, b
Romps, D. M.: Exact Expression for the Lifting Condensation Level, J. Atmos. Sci., 74, 3891–3900, https://doi.org/10.1175/JAS-D-17-0102.1,
2017. a
Rose, T., Crewell, S., Löhnert, U., and Simmer, C.: A network suitable
microwave radiometer for operational monitoring of the cloudy atmosphere,
Atmos. Res., 75, 183–200, https://doi.org/10.1016/j.atmosres.2004.12.005,
2005. a
Satoh, M., Stevens, B., Judt, F., Khairoutdinov, M., Lin, S.-J., Putman, W. M.,
and Düben, P.: Global Cloud-Resolving Models, Current Climate Change
Reports, 5, 172–184, https://doi.org/10.1007/s40641-019-00131-0, 2019. a
Schneider, T., Teixeira, J., Bretherton, C. S., Brient, F., Pressel, K. G.,
Schär, C., and Siebesma, A. P.: Climate goals and computing the future of
clouds, Nat. Clim. Change, 7, 3–5, https://doi.org/10.1038/nclimate3190, 2017. a
Seifert, A. and Beheng, K. D.: A double-moment parameterization for simulating
autoconversion, accretion and selfcollection, Atmos. Res., 59–60,
265–281, https://doi.org/10.1016/S0169-8095(01)00126-0, 2001. a, b, c, d
Siebert, H., Beals, M., Bethke, J., Bierwirth, E., Conrath, T., Dieckmann, K., Ditas, F., Ehrlich, A., Farrell, D., Hartmann, S., Izaguirre, M. A., Katzwinkel, J., Nuijens, L., Roberts, G., Schäfer, M., Shaw, R. A., Schmeissner, T., Serikov, I., Stevens, B., Stratmann, F., Wehner, B., Wendisch, M., Werner, F., and Wex, H.: The fine-scale structure of the trade wind cumuli over Barbados – an introduction to the CARRIBA project, Atmos. Chem. Phys., 13, 10061–10077, https://doi.org/10.5194/acp-13-10061-2013, 2013. a
Siebesma, A. P., Bretherton, C. S., Brown, A., Chlond, A., Cuxart, J.,
Duynkerke, P. G., Jiang, H., Khairoutdinov, M., Lewellen, D., Moeng, C.-H.,
Sanchez, E., Stevens, B., and Stevens, D. E.: A Large Eddy Simulation
Intercomparison Study of Shallow Cumulus Convection, J.
Atmos. Sci., 60, 1201–1219,
https://doi.org/10.1175/1520-0469(2003)60<1201:ALESIS>2.0.CO;2,
2003. a
Stevens, B., Farrell, D., Hirsch, L., Jansen, F., Nuijens, L., Serikov, I.,
Brügmann, B., Forde, M., Linne, H., Lonitz, K., and Prospero, J. M.: The
Barbados Cloud Observatory: Anchoring Investigations of Clouds
and Circulation on the Edge of the ITCZ, B. Am.
Meteorol. Soc., 97, 787–801, https://doi.org/10.1175/BAMS-D-14-00247.1, 2015. a, b
Stevens, B., Brogniez, H., Kiemle, C., Lacour, J.-L., Crevoisier, C., and
Kiliani, J.: Structure and Dynamical Influence of Water Vapor in the Lower
Tropical Troposphere, Surv. Geophys., 38, 1371–1397,
https://doi.org/10.1007/s10712-017-9420-8, 2017. a, b
Stevens, B., Ament, F., Bony, S., Crewell, S., Ewald, F., Gross, S., Hansen,
A., Hirsch, L., Jacob, M., Kölling, T., Konow, H., Mayer, B., Wendisch, M.,
Wirth, M., Wolf, K., Bakan, S., Bauer-Pfundstein, M., Brueck, M., Delanoë,
J., Ehrlich, A., Farrell, D., Forde, M., Gödde, F., Grob, H., Hagen, M.,
Jäkel, E., Jansen, F., Klepp, C., Klingebiel, M., Mech, M., Peters, G.,
Rapp, M., Wing, A. A., and Zinner, T.: A High-Altitude Long-Range
Aircraft Configured as a Cloud Observatory: The NARVAL
Expeditions, B. Am. Meteorol. Soc., 100,
1061–1077, https://doi.org/10.1175/BAMS-D-18-0198.1, 2019. a, b, c, d
Stevens, B., Acquistapace, C., Hansen, A., Heinze, R., Klinger, C., Klocke, D.,
Rybka, H., Schubotz, W., Windmiller, J., Adamidis, P., Arka, I., Barlakas,
V., Biercamp, J., Brueck, M., Brune, S., Buehler, S. A., Burkhardt, U.,
Cioni, G., Costa-surós, M., Crewell, S., Crüger, T., Deneke, H.,
Friederichs, P., Henken, C. C., Hohenegger, C., Jacob, M., Jakub, F.,
Kalthoff, N., Köhler, M., Laar, T. W. v., Li, P., Löhnert, U., Macke, A.,
Madenach, N., Mayer, B., Nam, C., Naumann, A. K., Peters, K., Poll, S.,
Quaas, J., Röber, N., Rochetin, N., Scheck, L., Schemann, V., Schnitt, S.,
Seifert, A., Senf, F., Shapkalijevski, M., Simmer, C., Singh, S., Sourdeval,
O., Spickermann, D., Strandgren, J., Tessiot, O., Vercauteren, N., Vial, J.,
Voigt, A., and Zängl, G.: The Added Value of Large-eddy and Storm-resolving
Models for Simulating Clouds and Precipitation, J. Meteorol.
Soc. Jpn. Ser. II, 98, 395–435, https://doi.org/10.2151/jmsj.2020-021, 2020. a
Stubenrauch, C. J., Rossow, W. B., Kinne, S., Ackerman, S., Cesana, G.,
Chepfer, H., Di Girolamo, L., Getzewich, B., Guignard, A., Heidinger, A.,
Maddux, B. C., Menzel, W. P., Minnis, P., Pearl, C., Platnick, S., Poulsen,
C., Riedi, J., Sun-Mack, S., Walther, A., Winker, D., Zeng, S., and Zhao, G.:
Assessment of Global Cloud Datasets from Satellites: Project and
Database Initiated by the GEWEX Radiation Panel, B.
Am. Meteorol. Soc., 94, 1031–1049,
https://doi.org/10.1175/BAMS-D-12-00117.1, 2013. a, b
Vaisala: Vaisala RD94 Dropsonde Datasheet, Technical data, Vaisala,
available at: https://www.vaisala.com/sites/default/files/documents/RD94-Datasheet-B210936EN-B.pdf (last access: 20 November 2020),
2017. a
van Zanten, M. C., Stevens, B., Nuijens, L., Siebesma, A. P., Ackerman, A. S.,
Burnet, F., Cheng, A., Couvreux, F., Jiang, H., Khairoutdinov, M., Kogan, Y.,
Lewellen, D. C., Mechem, D., Nakamura, K., Noda, A., Shipway, B. J.,
Slawinska, J., Wang, S., and Wyszogrodzki, A.: Controls on precipitation and
cloudiness in simulations of trade-wind cumulus as observed during RICO,
J. Adv. Model. Earth Sy., 3, M06001, https://doi.org/10.1029/2011MS000056,
2011. a, b
Vogel, R., Nuijens, L., and Stevens, B.: Influence of deepening and mesoscale
organization of shallow convection on stratiform cloudiness in the downstream
trades, Q. J. Roy. Meteor. Soc., 146, 174–185,
https://doi.org/10.1002/qj.3664, 2020. a, b, c
Wentz, F. J. and Meissner, T.: Algorithm Theoretical Basis Document (ATBD),
Version 2, AMSR Ocean Algorithm, Tech. rep., Remote Sensing Systems,
available at: http://images.remss.com/papers/rsstech/2000_121599A-1_Wentz_AMSR_Ocean_Algorithm_ATBD_Version2.pdf (last access: 20 November 2020),
2000. a
Wirth, M., Fix, A., Mahnke, P., Schwarzer, H., Schrandt, F., and Ehret, G.: The
airborne multi-wavelength water vapor differential absorption lidar WALES:
system design and performance, Appl. Phys. B, 96, 201–213,
https://doi.org/10.1007/s00340-009-3365-7, 2009. a
Wolf, K., Ehrlich, A., Jacob, M., Crewell, S., Wirth, M., and Wendisch, M.: Improvement of airborne retrievals of cloud droplet number concentration of trade wind cumulus using a synergetic approach, Atmos. Meas. Tech., 12, 1635–1658, https://doi.org/10.5194/amt-12-1635-2019, 2019. a
Wood, R., O, K.-T., Bretherton, C. S., Mohrmann, J., Albrecht, B. A., Zuidema,
P., Ghate, V., Schwartz, C., Eloranta, E., Glienke, S., Shaw, R. A., Fugal,
J., and Minnis, P.: Ultraclean Layers and Optically Thin Clouds in the
Stratocumulus-to-Cumulus Transition. Part I: Observations, J.
Atmos. Sci. 75, 1631–1652, https://doi.org/10.1175/JAS-D-17-0213.1, 2018. a, b, c
Wyant, M. C., Bretherton, C. S., Rand, H. A., and Stevens, D. E.: Numerical
Simulations and a Conceptual Model of the Stratocumulus to Trade
Cumulus Transition, J. Atmos. Sci., 54, 168–192,
https://doi.org/10.1175/1520-0469(1997)054<0168:NSAACM>2.0.CO;2, 1997. a
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON
(ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M:
Description of the non-hydrostatic dynamical core, Q. J.
Roy. Meteor. Soc., 141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a
Short summary
We compare clouds in different cloud-resolving atmosphere simulations with airborne remote sensing observations. The focus is on warm shallow clouds in the Atlantic trade wind region. Those clouds are climatologically important but challenging for climate models. We use forward operators to apply instrument-specific thresholds for cloud detection to model outputs. In this comparison, the higher-resolution model better reproduces the layered cloud structure.
We compare clouds in different cloud-resolving atmosphere simulations with airborne remote...
