Articles | Volume 14, issue 1
https://doi.org/10.5194/gmd-14-43-2021
© Author(s) 2021. 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-14-43-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
06 Jan 2021
Methods for assessment of models |
| 06 Jan 2021
| 06 Jan 2021
Ground-based lidar processing and simulator framework for comparing models and observations (ALCF 1.0)
School of Physical and Chemical Sciences, University of Canterbury, Christchurch, New Zealand
Adrian J. McDonald
School of Physical and Chemical Sciences, University of Canterbury, Christchurch, New Zealand
Olaf Morgenstern
National Institute of Water & Atmospheric Research (NIWA), Wellington, New Zealand
Richard Querel
National Institute of Water & Atmospheric Research (NIWA), Lauder, New Zealand
Israel Silber
Department of Meteorology and Atmospheric Science, Pennsylvania State University, PA, USA
Connor J. Flynn
School of Meteorology, University of Oklahoma, Norman, OK, USA
Related authors
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
EGUsphere, https://doi.org/10.5194/egusphere-2025-509, https://doi.org/10.5194/egusphere-2025-509, 2025
Short summary
Short summary
The nextGEMS project developed two Earth system models that resolve processes of the order of 10 km, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS performed simulations with coupled ocean, land, and atmosphere over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
Zhangcheng Pei, Sonya L. Fiddes, W. John R. French, Simon P. Alexander, Marc D. Mallet, Peter Kuma, and Adrian McDonald
Atmos. Chem. Phys., 23, 14691–14714, https://doi.org/10.5194/acp-23-14691-2023, https://doi.org/10.5194/acp-23-14691-2023, 2023
Short summary
Short summary
In this paper, we use ground-based observations to evaluate a climate model and a satellite product in simulating surface radiation and investigate how radiation biases are influenced by cloud properties over the Southern Ocean. We find that significant radiation biases exist in both the model and satellite. The cloud fraction and cloud occurrence play an important role in affecting radiation biases. We suggest further development for the model and satellite using ground-based observations.
Peter Kuma, Frida A.-M. Bender, Alex Schuddeboom, Adrian J. McDonald, and Øyvind Seland
Atmos. Chem. Phys., 23, 523–549, https://doi.org/10.5194/acp-23-523-2023, https://doi.org/10.5194/acp-23-523-2023, 2023
Short summary
Short summary
We present a machine learning method for determining cloud types in climate model output and satellite observations based on ground observations of cloud genera. We analyse cloud type biases and changes with temperature in climate models and show that the bias is anticorrelated with climate sensitivity. Models simulating decreasing stratiform and increasing cumuliform clouds with increased CO2 concentration tend to have higher climate sensitivity than models simulating the opposite tendencies.
Adrien Guyot, Alain Protat, Simon P. Alexander, Andrew R. Klekociuk, Peter Kuma, and Adrian McDonald
Atmos. Meas. Tech., 15, 3663–3681, https://doi.org/10.5194/amt-15-3663-2022, https://doi.org/10.5194/amt-15-3663-2022, 2022
Short summary
Short summary
Ceilometers are instruments that are widely deployed as part of operational networks. They are usually not able to detect cloud phase. Here, we propose an evaluation of various methods to detect supercooled liquid water with ceilometer observations, using an extensive dataset from Davis, Antarctica. Our results highlight the possibility for ceilometers to detect supercooled liquid water in clouds.
Stefanie Kremser, Mike Harvey, Peter Kuma, Sean Hartery, Alexia Saint-Macary, John McGregor, Alex Schuddeboom, Marc von Hobe, Sinikka T. Lennartz, Alex Geddes, Richard Querel, Adrian McDonald, Maija Peltola, Karine Sellegri, Israel Silber, Cliff S. Law, Connor J. Flynn, Andrew Marriner, Thomas C. J. Hill, Paul J. DeMott, Carson C. Hume, Graeme Plank, Geoffrey Graham, and Simon Parsons
Earth Syst. Sci. Data, 13, 3115–3153, https://doi.org/10.5194/essd-13-3115-2021, https://doi.org/10.5194/essd-13-3115-2021, 2021
Short summary
Short summary
Aerosol–cloud interactions over the Southern Ocean are poorly understood and remain a major source of uncertainty in climate models. This study presents ship-borne measurements, collected during a 6-week voyage into the Southern Ocean in 2018, that are an important supplement to satellite-based measurements. For example, these measurements include data on low-level clouds and aerosol composition in the marine boundary layer, which can be used in climate model evaluation efforts.
Ethan R. Dale, Stefanie Kremser, Jordis S. Tradowsky, Greg E. Bodeker, Leroy J. Bird, Gustavo Olivares, Guy Coulson, Elizabeth Somervell, Woodrow Pattinson, Jonathan Barte, Jan-Niklas Schmidt, Nariefa Abrahim, Adrian J. McDonald, and Peter Kuma
Earth Syst. Sci. Data, 13, 2053–2075, https://doi.org/10.5194/essd-13-2053-2021, https://doi.org/10.5194/essd-13-2053-2021, 2021
Short summary
Short summary
MAPM is a project whose goal is to develop a method to infer particulate matter (PM) emissions maps from PM concentration measurements. In support of MAPM, we conducted a winter field campaign in New Zealand. In addition to two types of instruments measuring PM, an array of other meteorological sensors were deployed, measuring temperature and wind speed as well as probing the vertical structure of the lower atmosphere. In this article, we present the measurements taken during this campaign.
Peter Kuma, Adrian J. McDonald, Olaf Morgenstern, Simon P. Alexander, John J. Cassano, Sally Garrett, Jamie Halla, Sean Hartery, Mike J. Harvey, Simon Parsons, Graeme Plank, Vidya Varma, and Jonny Williams
Atmos. Chem. Phys., 20, 6607–6630, https://doi.org/10.5194/acp-20-6607-2020, https://doi.org/10.5194/acp-20-6607-2020, 2020
Short summary
Short summary
We evaluate clouds over the Southern Ocean in the climate model HadGEM3 and reanalysis MERRA-2 using ship-based ceilometer and radiosonde observations. We find the models underestimate cloud cover by 18–25 %, with clouds below 2 km dominant in reality but lacking in the models. We find a strong link between clouds, atmospheric stability and sea surface temperature in observations but not in the models, implying that sub-grid processes do not generate enough cloud in response to these conditions.
Ben Jolly, Peter Kuma, Adrian McDonald, and Simon Parsons
Atmos. Chem. Phys., 18, 9723–9739, https://doi.org/10.5194/acp-18-9723-2018, https://doi.org/10.5194/acp-18-9723-2018, 2018
Short summary
Short summary
Clouds in the Ross Sea and Ross Ice Shelf regions are examined using a combination of satellite observations from the CloudSat and CALIPSO satellite datasets. We show that previous studies may have included an artefact at high altitudes which under-estimated cloud occurrence. We also find that the meteorological regime is a stronger control of cloud occurrence, cloud type and cloud top than season over this region, though season is a strong control on the phase of cloud.
Logan Thomas Mitchell, Connor J. Flynn, Kristina Pistone, Samuel E. LeBlanc, K. Sebastian Schmidt, and Jens Redemann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-31, https://doi.org/10.5194/essd-2025-31, 2025
Preprint under review for ESSD
Short summary
Short summary
During 2016–2018, NASA conducted an airborne field campaign over the Southeast Atlantic Ocean to study biomass burning aerosols emitted from Southern African fires. These aerosols then interact with stratocumulus clouds over the Southeast Atlantic, which is difficult for climate models to account for. Our instrument, 4STAR, determines aerosol radiative properties. A dataset was already created for 2016, but additional quality control was required to address instrument issues for 2017 and 2018.
Fan Mei, Qi Zhang, Damao Zhang, Jerome D. Fast, Gourihar Kulkarni, Mikhail S. Pekour, Christopher R. Niedek, Susanne Glienke, Israel Silber, Beat Schmid, Jason M. Tomlinson, Hardeep S. Mehta, Xena Mansoura, Zezhen Cheng, Gregory W. Vandergrift, Nurun Nahar Lata, Swarup China, and Zihua Zhu
Atmos. Chem. Phys., 25, 3425–3444, https://doi.org/10.5194/acp-25-3425-2025, https://doi.org/10.5194/acp-25-3425-2025, 2025
Short summary
Short summary
This study highlights the unique capability of the ArcticShark, an uncrewed aerial system, in measuring vertically resolved atmospheric properties. Data from 32 research flights in 2023 reveal seasonal patterns and correlations with conventional measurements. The consistency and complementarity of in situ and remote sensing methods are highlighted. The study demonstrates the ArcticShark’s versatility in bridging data gaps and improving the understanding of vertical atmospheric structures.
Irina Petropavlovskikh, Jeannette D. Wild, Kari Abromitis, Peter Effertz, Koji Miyagawa, Lawrence E. Flynn, Eliane Maillard Barras, Robert Damadeo, Glen McConville, Bryan Johnson, Patrick Cullis, Sophie Godin-Beekmann, Gerard Ancellet, Richard Querel, Roeland Van Malderen, and Daniel Zawada
Atmos. Chem. Phys., 25, 2895–2936, https://doi.org/10.5194/acp-25-2895-2025, https://doi.org/10.5194/acp-25-2895-2025, 2025
Short summary
Short summary
Observational records show that stratospheric ozone is recovering in accordance with the implementation of the Montreal Protocol and its amendments. Natural ozone variability complicates the detection of small trends. This study optimizes a statistical model fit in ground-station-based observational records by adding parameters that interpret seasonal and long-term changes in atmospheric circulation and airmass mixing, which reduces uncertainties in detecting the stratospheric ozone recovery.
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
EGUsphere, https://doi.org/10.5194/egusphere-2025-509, https://doi.org/10.5194/egusphere-2025-509, 2025
Short summary
Short summary
The nextGEMS project developed two Earth system models that resolve processes of the order of 10 km, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS performed simulations with coupled ocean, land, and atmosphere over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
Abdulamid A. Fakoya, Jens Redemann, Pablo E. Saide, Lan Gao, Logan T. Mitchell, Calvin Howes, Amie Dobracki, Ian Chang, Gonzalo A. Ferrada, Kristina Pistone, Samuel E. Leblanc, Michal Segal-Rozenhaimer, Arthur J. Sedlacek III, Thomas Eck, Brent Holben, Pawan Gupta, Elena Lind, Paquita Zuidema, Gregory Carmichael, and Connor J. Flynn
EGUsphere, https://doi.org/10.5194/egusphere-2024-3197, https://doi.org/10.5194/egusphere-2024-3197, 2025
Short summary
Short summary
Tiny atmospheric particles from wildfire smoke impact climate by interacting with sunlight and clouds, the extent of which is uncertain due to gaps in understanding how smoke changes over time. We developed a new method using remote sensing instruments to track how these particles evolve during atmospheric transport. Our results show that the ability of these particles to absorb sunlight increased as they travel. This discovery could help improve predictions of future climate scenarios.
Roeland Van Malderen, Anne M. Thompson, Debra E. Kollonige, Ryan M. Stauffer, Herman G. J. Smit, Eliane Maillard Barras, Corinne Vigouroux, Irina Petropavlovskikh, Thierry Leblanc, Valérie Thouret, Pawel Wolff, Peter Effertz, David W. Tarasick, Deniz Poyraz, Gérard Ancellet, Marie-Renée De Backer, Stéphanie Evan, Victoria Flood, Matthias M. Frey, James W. Hannigan, José L. Hernandez, Marco Iarlori, Bryan J. Johnson, Nicholas Jones, Rigel Kivi, Emmanuel Mahieu, Glen McConville, Katrin Müller, Tomoo Nagahama, Justus Notholt, Ankie Piters, Natalia Prats, Richard Querel, Dan Smale, Wolfgang Steinbrecht, Kimberly Strong, and Ralf Sussmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-3736, https://doi.org/10.5194/egusphere-2024-3736, 2025
Short summary
Short summary
Tropospheric ozone is an important greenhouse gas and is an air pollutant. The time variability of tropospheric ozone is mainly driven by anthropogenic emissions. In this paper, we study the distribution and time variability of ozone from harmonized ground-based observations from five different measurement techniques. Our findings will provide clear standard references for atmospheric models and evolving tropospheric ozone satellite data for the 2000–2022 period.
Roeland Van Malderen, Zhou Zang, Kai-Lan Chang, Robin Björklund, Owen R. Cooper, Jane Liu, Eliane Maillard Barras, Corinne Vigouroux, Irina Petropavlovskikh, Thierry Leblanc, Valérie Thouret, Pawel Wolff, Peter Effertz, Audrey Gaudel, David W. Tarasick, Herman G. J. Smit, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Deniz Poyraz, Gérard Ancellet, Marie-Renée De Backer, Matthias M. Frey, James W. Hannigan, José L. Hernandez, Bryan J. Johnson, Nicholas Jones, Rigel Kivi, Emmanuel Mahieu, Isamu Morino, Glen McConville, Katrin Müller, Isao Murata, Justus Notholt, Ankie Piters, Maxime Prignon, Richard Querel, Vincenzo Rizi, Dan Smale, Wolfgang Steinbrecht, Kimberly Strong, and Ralf Sussmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-3745, https://doi.org/10.5194/egusphere-2024-3745, 2025
Short summary
Short summary
Tropospheric ozone is an important greenhouse gas and an air pollutant, whose distribution and time variability is mainly governed by anthropogenic emissions and dynamics. In this paper, we assess regional trends of tropospheric ozone column amounts, based on two different approaches of merging or synthesizing ground-based observations and their trends within specific regions. Our findings clearly demonstrate regional trend differences, but also consistently higher pre- than post-COVID trends.
Israel Silber, Jennifer M. Comstock, Michael R. Kieburtz, and Lynn M. Russell
Earth Syst. Sci. Data, 17, 29–42, https://doi.org/10.5194/essd-17-29-2025, https://doi.org/10.5194/essd-17-29-2025, 2025
Short summary
Short summary
We present ARMTRAJ, a set of multipurpose trajectory datasets, which augments cloud, aerosol, and boundary layer studies utilizing the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility data. ARMTRAJ data include ensemble run statistics that enhance consistency and serve as uncertainty metrics for air mass coordinates and state variables. ARMTRAJ will soon become a near real-time product that will accompany past, ongoing, and future ARM deployments.
Robin Björklund, Corinne Vigouroux, Peter Effertz, Omaira E. García, Alex Geddes, James Hannigan, Koji Miyagawa, Michael Kotkamp, Bavo Langerock, Gerald Nedoluha, Ivan Ortega, Irina Petropavlovskikh, Deniz Poyraz, Richard Querel, John Robinson, Hisako Shiona, Dan Smale, Penny Smale, Roeland Van Malderen, and Martine De Mazière
Atmos. Meas. Tech., 17, 6819–6849, https://doi.org/10.5194/amt-17-6819-2024, https://doi.org/10.5194/amt-17-6819-2024, 2024
Short summary
Short summary
Different ground-based ozone measurements from the last 2 decades at Lauder are compared to each other. We want to know why different trends have been observed in the stratosphere. Also, the quality and relevance of tropospheric datasets need to be evaluated. While remaining drifts are still present, our study explains roughly half of the differences in observed trends in previous studies and shows the necessity for continuous review and improvement of the measurements.
Yunqian Zhu, Hideharu Akiyoshi, Valentina Aquila, Elisabeth Asher, Ewa M. Bednarz, Slimane Bekki, Christoph Brühl, Amy H. Butler, Parker Case, Simon Chabrillat, Gabriel Chiodo, Margot Clyne, Lola Falletti, Peter R. Colarco, Eric Fleming, Andrin Jörimann, Mahesh Kovilakam, Gerbrand Koren, Ales Kuchar, Nicolas Lebas, Qing Liang, Cheng-Cheng Liu, Graham Mann, Michael Manyin, Marion Marchand, Olaf Morgenstern, Paul Newman, Luke D. Oman, Freja F. Østerstrøm, Yifeng Peng, David Plummer, Ilaria Quaglia, William Randel, Samuel Rémy, Takashi Sekiya, Stephen Steenrod, Timofei Sukhodolov, Simone Tilmes, Kostas Tsigaridis, Rei Ueyama, Daniele Visioni, Xinyue Wang, Shingo Watanabe, Yousuke Yamashita, Pengfei Yu, Wandi Yu, Jun Zhang, and Zhihong Zhuo
EGUsphere, https://doi.org/10.5194/egusphere-2024-3412, https://doi.org/10.5194/egusphere-2024-3412, 2024
Short summary
Short summary
To understand the climate impact of the 2022 Hunga volcanic eruption, we developed a climate model-observation comparison project. The paper describes the protocols and models that participate in the experiments. We designed several experiments to achieve our goal of this activity: 1. evaluate the climate model performance; 2. understand the Earth system responses to this eruption.
Abigail S. Williams, Jeramy L. Dedrick, Lynn M. Russell, Florian Tornow, Israel Silber, Ann M. Fridlind, Benjamin Swanson, Paul J. DeMott, Paul Zieger, and Radovan Krejci
Atmos. Chem. Phys., 24, 11791–11805, https://doi.org/10.5194/acp-24-11791-2024, https://doi.org/10.5194/acp-24-11791-2024, 2024
Short summary
Short summary
The measured aerosol size distribution modes reveal distinct properties characteristic of cold-air outbreaks in the Norwegian Arctic. We find higher sea spray number concentrations, smaller Hoppel minima, lower effective supersaturations, and accumulation-mode particle scavenging during cold-air outbreaks. These results advance our understanding of cold-air outbreak aerosol–cloud interactions in order to improve their accurate representation in models.
Luke Edgar Whitehead, Adrian James McDonald, and Adrien Guyot
Atmos. Meas. Tech., 17, 5765–5784, https://doi.org/10.5194/amt-17-5765-2024, https://doi.org/10.5194/amt-17-5765-2024, 2024
Short summary
Short summary
Supercooled liquid water cloud is important to represent in weather and climate models, particularly in the Southern Hemisphere. Previous work has developed a new machine learning method for measuring supercooled liquid water in Antarctic clouds using simple lidar observations. We evaluate this technique using a lidar dataset from Christchurch, New Zealand, and develop an updated algorithm for accurate supercooled liquid water detection at mid-latitudes.
Evgueni Kassianov, Connor J. Flynn, James C. Barnard, Brian D. Ermold, and Jennifer M. Comstock
Atmos. Meas. Tech., 17, 4997–5013, https://doi.org/10.5194/amt-17-4997-2024, https://doi.org/10.5194/amt-17-4997-2024, 2024
Short summary
Short summary
Conventional ground-based radiometers commonly measure solar radiation at a few wavelengths within a narrow spectral range. These limitations prevent improved retrievals of aerosol, cloud, and surface characteristics. To address these limitations, an advanced ground-based radiometer with expanded spectral coverage and hyperspectral capability is introduced. Its good performance is demonstrated using reference data collected over three coastal regions with diverse types of aerosols and clouds.
Olaf Morgenstern
Atmos. Chem. Phys., 24, 8105–8123, https://doi.org/10.5194/acp-24-8105-2024, https://doi.org/10.5194/acp-24-8105-2024, 2024
Short summary
Short summary
I use errors in climate model simulations to derive correction factors for the impacts of greenhouse gases and particles that bring these simulated temperature fields into agreement with an observational reconstruction of the Earth's temperature. On average across eight models, a reduction by about one-half of the particle-induced cooling would be required, causing only 0.24 K of cooling since 1850–1899. The greenhouse gas warming simulated by several highly sensitive models would also reduce.
Nelson Bègue, Alexandre Baron, Gisèle Krysztofiak, Gwenaël Berthet, Corinna Kloss, Fabrice Jégou, Sergey Khaykin, Marion Ranaivombola, Tristan Millet, Thierry Portafaix, Valentin Duflot, Philippe Keckhut, Hélène Vérèmes, Guillaume Payen, Mahesh Kumar Sha, Pierre-François Coheur, Cathy Clerbaux, Michaël Sicard, Tetsu Sakai, Richard Querel, Ben Liley, Dan Smale, Isamu Morino, Osamu Uchino, Tomohiro Nagai, Penny Smale, John Robinson, and Hassan Bencherif
Atmos. Chem. Phys., 24, 8031–8048, https://doi.org/10.5194/acp-24-8031-2024, https://doi.org/10.5194/acp-24-8031-2024, 2024
Short summary
Short summary
During the 2020 austral summer, the pristine atmosphere of the southwest Indian Ocean basin experienced significant perturbations. Numerical models indicated that the lower-stratospheric aerosol content was influenced by the intense and persistent stratospheric aerosol layer generated during the 2019–2020 extreme Australian bushfire events. Ground-based observations at Réunion confirmed the simultaneous presence of African and Australian aerosol layers.
Grégory V. Cesana, Olivia Pierpaoli, Matteo Ottaviani, Linh Vu, Zhonghai Jin, and Israel Silber
Atmos. Chem. Phys., 24, 7899–7909, https://doi.org/10.5194/acp-24-7899-2024, https://doi.org/10.5194/acp-24-7899-2024, 2024
Short summary
Short summary
Better characterizing the relationship between sea ice and clouds is key to understanding Arctic climate because clouds and sea ice affect surface radiation and modulate Arctic surface warming. Our results indicate that Arctic liquid clouds robustly increase in response to sea ice decrease. This increase has a cooling effect on the surface because more solar radiation is reflected back to space, and it should contribute to dampening future Arctic surface warming.
Kelly A. Balmes, Laura D. Riihimaki, John Wood, Connor Flynn, Adam Theisen, Michael Ritsche, Lynn Ma, Gary B. Hodges, and Christian Herrera
Atmos. Meas. Tech., 17, 3783–3807, https://doi.org/10.5194/amt-17-3783-2024, https://doi.org/10.5194/amt-17-3783-2024, 2024
Short summary
Short summary
A new hyperspectral radiometer (HSR1) was deployed and evaluated in the central United States (northern Oklahoma). The HSR1 total spectral irradiance agreed well with nearby existing instruments, but the diffuse spectral irradiance was slightly smaller. The HSR1-retrieved aerosol optical depth (AOD) also agreed well with other retrieved AODs. The HSR1 performance is encouraging: new hyperspectral knowledge is possible that could inform atmospheric process understanding and weather forecasting.
Guang Zeng, Richard Querel, Hisako Shiona, Deniz Poyraz, Roeland Van Malderen, Alex Geddes, Penny Smale, Dan Smale, John Robinson, and Olaf Morgenstern
Atmos. Chem. Phys., 24, 6413–6432, https://doi.org/10.5194/acp-24-6413-2024, https://doi.org/10.5194/acp-24-6413-2024, 2024
Short summary
Short summary
We present a homogenised ozonesonde record (1987–2020) for Lauder, a Southern Hemisphere mid-latitude site; identify factors driving ozone trends; and attribute them to anthropogenic forcings using statistical analysis and model simulations. We find that significant negative lower-stratospheric ozone trends identified at Lauder are associated with an increase in tropopause height and that CO2-driven dynamical changes have played an increasingly important role in driving ozone trends.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
Short summary
Short summary
We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Hiren T. Jethva, Omar Torres, Richard A. Ferrare, Sharon P. Burton, Anthony L. Cook, David B. Harper, Chris A. Hostetler, Jens Redemann, Vinay Kayetha, Samuel LeBlanc, Kristina Pistone, Logan Mitchell, and Connor J. Flynn
Atmos. Meas. Tech., 17, 2335–2366, https://doi.org/10.5194/amt-17-2335-2024, https://doi.org/10.5194/amt-17-2335-2024, 2024
Short summary
Short summary
We introduce a novel synergy algorithm applied to ORALCES airborne measurements of above-cloud aerosol optical depth and UV–Vis satellite observations from OMI and MODIS to retrieve spectral aerosol single-scattering albedo of lofted layers of carbonaceous smoke aerosols over clouds. The development of the proposed aerosol–cloud algorithm implies a possible synergy of CALIOP and OMI–MODIS passive sensors to deduce a global product of AOD and SSA of absorbing aerosols above clouds.
Alexander Geddes, Ben Liley, Richard McKenzie, Michael Kotkamp, and Richard Querel
Atmos. Meas. Tech., 17, 827–838, https://doi.org/10.5194/amt-17-827-2024, https://doi.org/10.5194/amt-17-827-2024, 2024
Short summary
Short summary
In this paper we describe a unique spectrometer that has been developed and tested over 10 years at Lauder, New Zealand. The spectrometer in question, UV2, makes alternating measurements of global UV and direct sun UV irradiance. After an assessment of the instrument performance, we compare the ozone and aerosol optical depth derived from UV2 to other independent measurements, finding excellent agreement suggesting that UV2 could supersede these measurements, particularly for ozone.
Yusuf A. Bhatti, Laura E. Revell, Alex J. Schuddeboom, Adrian J. McDonald, Alex T. Archibald, Jonny Williams, Abhijith U. Venugopal, Catherine Hardacre, and Erik Behrens
Atmos. Chem. Phys., 23, 15181–15196, https://doi.org/10.5194/acp-23-15181-2023, https://doi.org/10.5194/acp-23-15181-2023, 2023
Short summary
Short summary
Aerosols are a large source of uncertainty over the Southern Ocean. A dominant source of sulfate aerosol in this region is dimethyl sulfide (DMS), which is poorly simulated by climate models. We show the sensitivity of simulated atmospheric DMS to the choice of oceanic DMS data set and emission scheme. We show that oceanic DMS has twice the influence on atmospheric DMS than the emission scheme. Simulating DMS more accurately in climate models will help to constrain aerosol uncertainty.
Zhangcheng Pei, Sonya L. Fiddes, W. John R. French, Simon P. Alexander, Marc D. Mallet, Peter Kuma, and Adrian McDonald
Atmos. Chem. Phys., 23, 14691–14714, https://doi.org/10.5194/acp-23-14691-2023, https://doi.org/10.5194/acp-23-14691-2023, 2023
Short summary
Short summary
In this paper, we use ground-based observations to evaluate a climate model and a satellite product in simulating surface radiation and investigate how radiation biases are influenced by cloud properties over the Southern Ocean. We find that significant radiation biases exist in both the model and satellite. The cloud fraction and cloud occurrence play an important role in affecting radiation biases. We suggest further development for the model and satellite using ground-based observations.
Marina Friedel, Gabriel Chiodo, Timofei Sukhodolov, James Keeble, Thomas Peter, Svenja Seeber, Andrea Stenke, Hideharu Akiyoshi, Eugene Rozanov, David Plummer, Patrick Jöckel, Guang Zeng, Olaf Morgenstern, and Béatrice Josse
Atmos. Chem. Phys., 23, 10235–10254, https://doi.org/10.5194/acp-23-10235-2023, https://doi.org/10.5194/acp-23-10235-2023, 2023
Short summary
Short summary
Previously, it has been suggested that springtime Arctic ozone depletion might worsen in the coming decades due to climate change, which might counteract the effect of reduced ozone-depleting substances. Here, we show with different chemistry–climate models that springtime Arctic ozone depletion will likely decrease in the future. Further, we explain why models show a large spread in the projected development of Arctic ozone depletion and use the model spread to constrain future projections.
McKenna W. Stanford, Ann M. Fridlind, Israel Silber, Andrew S. Ackerman, Greg Cesana, Johannes Mülmenstädt, Alain Protat, Simon Alexander, and Adrian McDonald
Atmos. Chem. Phys., 23, 9037–9069, https://doi.org/10.5194/acp-23-9037-2023, https://doi.org/10.5194/acp-23-9037-2023, 2023
Short summary
Short summary
Clouds play an important role in the Earth’s climate system as they modulate the amount of radiation that either reaches the surface or is reflected back to space. This study demonstrates an approach to robustly evaluate surface-based observations against a large-scale model. We find that the large-scale model precipitates too infrequently relative to observations, contrary to literature documentation suggesting otherwise based on satellite measurements.
Jonny Williams, Erik Behrens, Olaf Morgenstern, Peter Gibson, and Joao Teixeira
EGUsphere, https://doi.org/10.5194/egusphere-2023-1694, https://doi.org/10.5194/egusphere-2023-1694, 2023
Preprint withdrawn
Short summary
Short summary
We use open-source cyclone tracking software and state-of-the-art climate models to characterise present-day tropical cyclones – TCs – in the South Pacific before moving on to estimate how they may change in the future. A robust result of this work is the projection of future intensification of TCs. However, the question of their future occurrence frequency is less clear. Under extreme future warming scenarios, we postulate a possible increase in power dissipation per TC of up to 25 %.
Ian Chang, Lan Gao, Connor J. Flynn, Yohei Shinozuka, Sarah J. Doherty, Michael S. Diamond, Karla M. Longo, Gonzalo A. Ferrada, Gregory R. Carmichael, Patricia Castellanos, Arlindo M. da Silva, Pablo E. Saide, Calvin Howes, Zhixin Xue, Marc Mallet, Ravi Govindaraju, Qiaoqiao Wang, Yafang Cheng, Yan Feng, Sharon P. Burton, Richard A. Ferrare, Samuel E. LeBlanc, Meloë S. Kacenelenbogen, Kristina Pistone, Michal Segal-Rozenhaimer, Kerry G. Meyer, Ju-Mee Ryoo, Leonhard Pfister, Adeyemi A. Adebiyi, Robert Wood, Paquita Zuidema, Sundar A. Christopher, and Jens Redemann
Atmos. Chem. Phys., 23, 4283–4309, https://doi.org/10.5194/acp-23-4283-2023, https://doi.org/10.5194/acp-23-4283-2023, 2023
Short summary
Short summary
Abundant aerosols are present above low-level liquid clouds over the southeastern Atlantic during late austral spring. The model simulation differences in the proportion of aerosol residing in the planetary boundary layer and in the free troposphere can greatly affect the regional aerosol radiative effects. This study examines the aerosol loading and fractional aerosol loading in the free troposphere among various models and evaluates them against measurements from the NASA ORACLES campaign.
Francesca Gallo, Janek Uin, Kevin J. Sanchez, Richard H. Moore, Jian Wang, Robert Wood, Fan Mei, Connor Flynn, Stephen Springston, Eduardo B. Azevedo, Chongai Kuang, and Allison C. Aiken
Atmos. Chem. Phys., 23, 4221–4246, https://doi.org/10.5194/acp-23-4221-2023, https://doi.org/10.5194/acp-23-4221-2023, 2023
Short summary
Short summary
This study provides a summary statistic of multiday aerosol plume transport event influences on aerosol physical properties and the cloud condensation nuclei budget at the U.S. Department of Energy Atmospheric Radiation Measurement Facility in the eastern North Atlantic (ENA). An algorithm that integrates aerosol properties is developed and applied to identify multiday aerosol transport events. The influence of the aerosol plumes on aerosol populations at the ENA is successively assessed.
Ruhi S. Humphries, Melita D. Keywood, Jason P. Ward, James Harnwell, Simon P. Alexander, Andrew R. Klekociuk, Keiichiro Hara, Ian M. McRobert, Alain Protat, Joel Alroe, Luke T. Cravigan, Branka Miljevic, Zoran D. Ristovski, Robyn Schofield, Stephen R. Wilson, Connor J. Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Greg M. McFarquhar, Scott D. Chambers, Alastair G. Williams, and Alan D. Griffiths
Atmos. Chem. Phys., 23, 3749–3777, https://doi.org/10.5194/acp-23-3749-2023, https://doi.org/10.5194/acp-23-3749-2023, 2023
Short summary
Short summary
Observations of aerosols in pristine regions are rare but are vital to constraining the natural baseline from which climate simulations are calculated. Here we present recent seasonal observations of aerosols from the Southern Ocean and contrast them with measurements from Antarctica, Australia and regionally relevant voyages. Strong seasonal cycles persist, but striking differences occur at different latitudes. This study highlights the need for more long-term observations in remote regions.
Udo Frieß, Karin Kreher, Richard Querel, Holger Schmithüsen, Dan Smale, Rolf Weller, and Ulrich Platt
Atmos. Chem. Phys., 23, 3207–3232, https://doi.org/10.5194/acp-23-3207-2023, https://doi.org/10.5194/acp-23-3207-2023, 2023
Short summary
Short summary
Reactive bromine compounds, emitted by the sea ice during polar spring, play an important role in the atmospheric chemistry of the coastal regions of Antarctica. We investigate the sources and impacts of reactive bromine in detail using many years of measurements at two Antarctic sites located at opposite sides of the Antarctic continent. Using a multitude of meteorological observations, we were able to identify the main triggers and source regions for reactive bromine in Antarctica.
Peter Kuma, Frida A.-M. Bender, Alex Schuddeboom, Adrian J. McDonald, and Øyvind Seland
Atmos. Chem. Phys., 23, 523–549, https://doi.org/10.5194/acp-23-523-2023, https://doi.org/10.5194/acp-23-523-2023, 2023
Short summary
Short summary
We present a machine learning method for determining cloud types in climate model output and satellite observations based on ground observations of cloud genera. We analyse cloud type biases and changes with temperature in climate models and show that the bias is anticorrelated with climate sensitivity. Models simulating decreasing stratiform and increasing cumuliform clouds with increased CO2 concentration tend to have higher climate sensitivity than models simulating the opposite tendencies.
Paul A. Barrett, Steven J. Abel, Hugh Coe, Ian Crawford, Amie Dobracki, James Haywood, Steve Howell, Anthony Jones, Justin Langridge, Greg M. McFarquhar, Graeme J. Nott, Hannah Price, Jens Redemann, Yohei Shinozuka, Kate Szpek, Jonathan W. Taylor, Robert Wood, Huihui Wu, Paquita Zuidema, Stéphane Bauguitte, Ryan Bennett, Keith Bower, Hong Chen, Sabrina Cochrane, Michael Cotterell, Nicholas Davies, David Delene, Connor Flynn, Andrew Freedman, Steffen Freitag, Siddhant Gupta, David Noone, Timothy B. Onasch, James Podolske, Michael R. Poellot, Sebastian Schmidt, Stephen Springston, Arthur J. Sedlacek III, Jamie Trembath, Alan Vance, Maria A. Zawadowicz, and Jianhao Zhang
Atmos. Meas. Tech., 15, 6329–6371, https://doi.org/10.5194/amt-15-6329-2022, https://doi.org/10.5194/amt-15-6329-2022, 2022
Short summary
Short summary
To better understand weather and climate, it is vital to go into the field and collect observations. Often measurements take place in isolation, but here we compared data from two aircraft and one ground-based site. This was done in order to understand how well measurements made on one platform compared to those made on another. Whilst this is easy to do in a controlled laboratory setting, it is more challenging in the real world, and so these comparisons are as valuable as they are rare.
Frederic Tridon, Israel Silber, Alessandro Battaglia, Stefan Kneifel, Ann Fridlind, Petros Kalogeras, and Ranvir Dhillon
Atmos. Chem. Phys., 22, 12467–12491, https://doi.org/10.5194/acp-22-12467-2022, https://doi.org/10.5194/acp-22-12467-2022, 2022
Short summary
Short summary
The role of ice precipitation in the Earth water budget is not well known because ice particles are complex, and their formation involves intricate processes. Riming of ice crystals by supercooled water droplets is an efficient process, but little is known about its importance at high latitudes. In this work, by exploiting the deployment of an unprecedented number of remote sensing systems in Antarctica, we find that riming occurs at much lower temperatures compared with the mid-latitudes.
Sophie Godin-Beekmann, Niramson Azouz, Viktoria F. Sofieva, Daan Hubert, Irina Petropavlovskikh, Peter Effertz, Gérard Ancellet, Doug A. Degenstein, Daniel Zawada, Lucien Froidevaux, Stacey Frith, Jeannette Wild, Sean Davis, Wolfgang Steinbrecht, Thierry Leblanc, Richard Querel, Kleareti Tourpali, Robert Damadeo, Eliane Maillard Barras, René Stübi, Corinne Vigouroux, Carlo Arosio, Gerald Nedoluha, Ian Boyd, Roeland Van Malderen, Emmanuel Mahieu, Dan Smale, and Ralf Sussmann
Atmos. Chem. Phys., 22, 11657–11673, https://doi.org/10.5194/acp-22-11657-2022, https://doi.org/10.5194/acp-22-11657-2022, 2022
Short summary
Short summary
An updated evaluation up to 2020 of stratospheric ozone profile long-term trends at extrapolar latitudes based on satellite and ground-based records is presented. Ozone increase in the upper stratosphere is confirmed, with significant trends at most latitudes. In this altitude region, a very good agreement is found with trends derived from chemistry–climate model simulations. Observed and modelled trends diverge in the lower stratosphere, but the differences are non-significant.
Samuel E. LeBlanc, Michal Segal-Rozenhaimer, Jens Redemann, Connor Flynn, Roy R. Johnson, Stephen E. Dunagan, Robert Dahlgren, Jhoon Kim, Myungje Choi, Arlindo da Silva, Patricia Castellanos, Qian Tan, Luke Ziemba, Kenneth Lee Thornhill, and Meloë Kacenelenbogen
Atmos. Chem. Phys., 22, 11275–11304, https://doi.org/10.5194/acp-22-11275-2022, https://doi.org/10.5194/acp-22-11275-2022, 2022
Short summary
Short summary
Airborne observations of atmospheric particles and pollution over Korea during a field campaign in May–June 2016 showed that the smallest atmospheric particles are present in the lowest 2 km of the atmosphere. The aerosol size is more spatially variable than optical thickness. We show this with remote sensing (4STAR), in situ (LARGE) observations, satellite measurements (GOCI), and modeled properties (MERRA-2), and it is contrary to the current understanding.
Haochi Che, Michal Segal-Rozenhaimer, Lu Zhang, Caroline Dang, Paquita Zuidema, Arthur J. Sedlacek III, Xiaoye Zhang, and Connor Flynn
Atmos. Chem. Phys., 22, 8767–8785, https://doi.org/10.5194/acp-22-8767-2022, https://doi.org/10.5194/acp-22-8767-2022, 2022
Short summary
Short summary
A 17-month in situ study on Ascension Island found low single-scattering albedo and strong absorption enhancement of the marine boundary layer aerosols during biomass burnings on the African continent, along with apparent patterns of regular monthly variability. We further discuss the characteristics and drivers behind these changes and find that biomass burning conditions in Africa may be the main factor influencing the optical properties of marine boundary aerosols.
Adrien Guyot, Alain Protat, Simon P. Alexander, Andrew R. Klekociuk, Peter Kuma, and Adrian McDonald
Atmos. Meas. Tech., 15, 3663–3681, https://doi.org/10.5194/amt-15-3663-2022, https://doi.org/10.5194/amt-15-3663-2022, 2022
Short summary
Short summary
Ceilometers are instruments that are widely deployed as part of operational networks. They are usually not able to detect cloud phase. Here, we propose an evaluation of various methods to detect supercooled liquid water with ceilometer observations, using an extensive dataset from Davis, Antarctica. Our results highlight the possibility for ceilometers to detect supercooled liquid water in clouds.
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Andreas Richter, Pieter Valks, Ramina Alwarda, Kristof Bognar, Udo Frieß, José Granville, Myojeong Gu, Paul Johnston, Cristina Prados-Roman, Richard Querel, Kimberly Strong, Thomas Wagner, Folkard Wittrock, and Margarita Yela Gonzalez
Atmos. Meas. Tech., 15, 3439–3463, https://doi.org/10.5194/amt-15-3439-2022, https://doi.org/10.5194/amt-15-3439-2022, 2022
Short summary
Short summary
We report on the GOME-2A and GOME-2B OClO dataset (2007 to 2016, from the EUMETSAT's AC SAF) validation using data from nine NDACC zenith-scattered-light DOAS (ZSL-DOAS) instruments distributed in both the Arctic and Antarctic. Specific sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings and their typical errors. Good agreement is found for both the inter-annual variability and the overall OClO seasonal behavior.
Alex R. Aves, Laura E. Revell, Sally Gaw, Helena Ruffell, Alex Schuddeboom, Ngaire E. Wotherspoon, Michelle LaRue, and Adrian J. McDonald
The Cryosphere, 16, 2127–2145, https://doi.org/10.5194/tc-16-2127-2022, https://doi.org/10.5194/tc-16-2127-2022, 2022
Short summary
Short summary
This study confirms the presence of microplastics in Antarctic snow, highlighting the extent of plastic pollution globally. Fresh snow was collected from Ross Island, Antarctica, and subsequent analysis identified an average of 29 microplastic particles per litre of melted snow. The most likely source of these airborne microplastics is local scientific research stations; however, modelling shows their origin could have been up to 6000 km away.
Irina Petropavlovskikh, Koji Miyagawa, Audra McClure-Beegle, Bryan Johnson, Jeannette Wild, Susan Strahan, Krzysztof Wargan, Richard Querel, Lawrence Flynn, Eric Beach, Gerard Ancellet, and Sophie Godin-Beekmann
Atmos. Meas. Tech., 15, 1849–1870, https://doi.org/10.5194/amt-15-1849-2022, https://doi.org/10.5194/amt-15-1849-2022, 2022
Short summary
Short summary
The Montreal Protocol and its amendments assure the recovery of the stratospheric ozone layer that protects the Earth from harmful ultraviolet radiation. To monitor ozone recovery, multiple satellites and ground-based observational platforms collect ozone data. The changes in instruments can influence the continuation of the ozone data. We discuss a method to remove instrumental artifacts from ozone records to improve the internal consistency among multiple observational records.
Israel Silber, Robert C. Jackson, Ann M. Fridlind, Andrew S. Ackerman, Scott Collis, Johannes Verlinde, and Jiachen Ding
Geosci. Model Dev., 15, 901–927, https://doi.org/10.5194/gmd-15-901-2022, https://doi.org/10.5194/gmd-15-901-2022, 2022
Short summary
Short summary
The Earth Model Column Collaboratory (EMC2) is an open-source ground-based (and air- or space-borne) lidar and radar simulator and subcolumn generator designed for large-scale models, in particular climate models, applicable also for high-resolution models. EMC2 emulates measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. We demonstrate the use of EMC2 to compare AWARE measurements with the NASA GISS ModelE3 and LES.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Michal Segal Rozenhaimer, Meloë Kacenelenbogen, Yohei Shinozuka, Connor Flynn, Rich Ferrare, Sharon Burton, Chris Hostetler, Marc Mallet, and Paquita Zuidema
Atmos. Meas. Tech., 15, 61–77, https://doi.org/10.5194/amt-15-61-2022, https://doi.org/10.5194/amt-15-61-2022, 2022
Short summary
Short summary
This work presents heating rates derived from aircraft observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS). We separate the total heating rates into aerosol and gas (primarily water vapor) absorption and explore some of the co-variability of heating rate profiles and their primary drivers, leading to the development of a new concept: the heating rate efficiency (HRE; the heating rate per unit aerosol extinction).
Nora Mettig, Mark Weber, Alexei Rozanov, Carlo Arosio, John P. Burrows, Pepijn Veefkind, Anne M. Thompson, Richard Querel, Thierry Leblanc, Sophie Godin-Beekmann, Rigel Kivi, and Matthew B. Tully
Atmos. Meas. Tech., 14, 6057–6082, https://doi.org/10.5194/amt-14-6057-2021, https://doi.org/10.5194/amt-14-6057-2021, 2021
Short summary
Short summary
TROPOMI is a nadir-viewing satellite that has observed global atmospheric trace gases at unprecedented spatial resolution since 2017. The retrieval of ozone profiles with high accuracy has been demonstrated using the TOPAS (Tikhonov regularised Ozone Profile retrievAl with SCIATRAN) algorithm and applying appropriate spectral corrections to TROPOMI UV data. Ozone profiles from TROPOMI were compared to ozonesonde and lidar profiles, showing an agreement to within 5 % in the stratosphere.
Ruhi S. Humphries, Melita D. Keywood, Sean Gribben, Ian M. McRobert, Jason P. Ward, Paul Selleck, Sally Taylor, James Harnwell, Connor Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Alain Protat, Simon P. Alexander, and Greg McFarquhar
Atmos. Chem. Phys., 21, 12757–12782, https://doi.org/10.5194/acp-21-12757-2021, https://doi.org/10.5194/acp-21-12757-2021, 2021
Short summary
Short summary
The Southern Ocean region is one of the most pristine in the world and serves as an important proxy for the pre-industrial atmosphere. Improving our understanding of the natural processes in this region is likely to result in the largest reductions in the uncertainty of climate and earth system models. In this paper we present a statistical summary of the latitudinal gradient of aerosol and cloud condensation nuclei concentrations obtained from five voyages spanning the Southern Ocean.
Konstantin Baibakov, Samuel LeBlanc, Keyvan Ranjbar, Norman T. O'Neill, Mengistu Wolde, Jens Redemann, Kristina Pistone, Shao-Meng Li, John Liggio, Katherine Hayden, Tak W. Chan, Michael J. Wheeler, Leonid Nichman, Connor Flynn, and Roy Johnson
Atmos. Chem. Phys., 21, 10671–10687, https://doi.org/10.5194/acp-21-10671-2021, https://doi.org/10.5194/acp-21-10671-2021, 2021
Short summary
Short summary
We find that the airborne measurements of the vertical extinction due to aerosols (aerosol optical depth, AOD) obtained in the Athabasca Oil Sands Region (AOSR) can significantly exceed ground-based values. This can have an effect on estimating the AOSR radiative impact and is relevant to satellite validation based on ground-based measurements. We also show that the AOD can marginally increase as the plumes are being transported away from the source and the new particles are being formed.
Stefanie Kremser, Mike Harvey, Peter Kuma, Sean Hartery, Alexia Saint-Macary, John McGregor, Alex Schuddeboom, Marc von Hobe, Sinikka T. Lennartz, Alex Geddes, Richard Querel, Adrian McDonald, Maija Peltola, Karine Sellegri, Israel Silber, Cliff S. Law, Connor J. Flynn, Andrew Marriner, Thomas C. J. Hill, Paul J. DeMott, Carson C. Hume, Graeme Plank, Geoffrey Graham, and Simon Parsons
Earth Syst. Sci. Data, 13, 3115–3153, https://doi.org/10.5194/essd-13-3115-2021, https://doi.org/10.5194/essd-13-3115-2021, 2021
Short summary
Short summary
Aerosol–cloud interactions over the Southern Ocean are poorly understood and remain a major source of uncertainty in climate models. This study presents ship-borne measurements, collected during a 6-week voyage into the Southern Ocean in 2018, that are an important supplement to satellite-based measurements. For example, these measurements include data on low-level clouds and aerosol composition in the marine boundary layer, which can be used in climate model evaluation efforts.
Kristina Pistone, Paquita Zuidema, Robert Wood, Michael Diamond, Arlindo M. da Silva, Gonzalo Ferrada, Pablo E. Saide, Rei Ueyama, Ju-Mee Ryoo, Leonhard Pfister, James Podolske, David Noone, Ryan Bennett, Eric Stith, Gregory Carmichael, Jens Redemann, Connor Flynn, Samuel LeBlanc, Michal Segal-Rozenhaimer, and Yohei Shinozuka
Atmos. Chem. Phys., 21, 9643–9668, https://doi.org/10.5194/acp-21-9643-2021, https://doi.org/10.5194/acp-21-9643-2021, 2021
Short summary
Short summary
Using aircraft-based measurements off the Atlantic coast of Africa, we found the springtime smoke plume was strongly correlated with the amount of water vapor in the atmosphere (more smoke indicated more humidity). We see the same general feature in satellite-assimilated and free-running models. Our analysis suggests this relationship is not caused by the burning but originates due to coincident continental meteorology plus fires. This air is transported over the ocean without further mixing.
Vidya Varma, Olaf Morgenstern, Kalli Furtado, Paul Field, and Jonny Williams
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-438, https://doi.org/10.5194/acp-2021-438, 2021
Revised manuscript not accepted
Short summary
Short summary
We introduce a simple parametrisation whereby the immersion freezing temperature in the model is linked to the mineral dust distribution through a diagnostic function, thus invoking regional differences in the nucleation temperatures instead of the global default value of −10 °C. This provides a functionality to mimic the role of Ice Nucleating Particles in the atmosphere on influencing the short-wave radiation over the Southern Ocean region by impacting the cloud phase.
Ethan R. Dale, Stefanie Kremser, Jordis S. Tradowsky, Greg E. Bodeker, Leroy J. Bird, Gustavo Olivares, Guy Coulson, Elizabeth Somervell, Woodrow Pattinson, Jonathan Barte, Jan-Niklas Schmidt, Nariefa Abrahim, Adrian J. McDonald, and Peter Kuma
Earth Syst. Sci. Data, 13, 2053–2075, https://doi.org/10.5194/essd-13-2053-2021, https://doi.org/10.5194/essd-13-2053-2021, 2021
Short summary
Short summary
MAPM is a project whose goal is to develop a method to infer particulate matter (PM) emissions maps from PM concentration measurements. In support of MAPM, we conducted a winter field campaign in New Zealand. In addition to two types of instruments measuring PM, an array of other meteorological sensors were deployed, measuring temperature and wind speed as well as probing the vertical structure of the lower atmosphere. In this article, we present the measurements taken during this campaign.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
Short summary
Short summary
Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Israel Silber, Ann M. Fridlind, Johannes Verlinde, Andrew S. Ackerman, Grégory V. Cesana, and Daniel A. Knopf
Atmos. Chem. Phys., 21, 3949–3971, https://doi.org/10.5194/acp-21-3949-2021, https://doi.org/10.5194/acp-21-3949-2021, 2021
Short summary
Short summary
Long-term ground-based radar and sounding measurements over Alaska (Antarctica) indicate that more than 85 % (75 %) of supercooled clouds are precipitating at cloud base and that 75 % (50 %) are precipitating to the surface. Such high prevalence is reconciled with lesser spaceborne estimates by considering radar sensitivity. Results provide a strong observational constraint for polar cloud processes in large-scale models.
Chaim I. Garfinkel, Ohad Harari, Shlomi Ziskin Ziv, Jian Rao, Olaf Morgenstern, Guang Zeng, Simone Tilmes, Douglas Kinnison, Fiona M. O'Connor, Neal Butchart, Makoto Deushi, Patrick Jöckel, Andrea Pozzer, and Sean Davis
Atmos. Chem. Phys., 21, 3725–3740, https://doi.org/10.5194/acp-21-3725-2021, https://doi.org/10.5194/acp-21-3725-2021, 2021
Short summary
Short summary
Water vapor is the dominant greenhouse gas in the atmosphere, and El Niño is the dominant mode of variability in the ocean–atmosphere system. The connection between El Niño and water vapor above ~ 17 km is unclear, with single-model studies reaching a range of conclusions. This study examines this connection in 12 different models. While there are substantial differences among the models, all models appear to capture the fundamental physical processes correctly.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
Short summary
Short summary
Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Fiona M. O'Connor, N. Luke Abraham, Mohit Dalvi, Gerd A. Folberth, Paul T. Griffiths, Catherine Hardacre, Ben T. Johnson, Ron Kahana, James Keeble, Byeonghyeon Kim, Olaf Morgenstern, Jane P. Mulcahy, Mark Richardson, Eddy Robertson, Jeongbyn Seo, Sungbo Shim, João C. Teixeira, Steven T. Turnock, Jonny Williams, Andrew J. Wiltshire, Stephanie Woodward, and Guang Zeng
Atmos. Chem. Phys., 21, 1211–1243, https://doi.org/10.5194/acp-21-1211-2021, https://doi.org/10.5194/acp-21-1211-2021, 2021
Short summary
Short summary
This paper calculates how changes in emissions and/or concentrations of different atmospheric constituents since the pre-industrial era have altered the Earth's energy budget at the present day using a metric called effective radiative forcing. The impact of land use change is also assessed. We find that individual contributions do not add linearly, and different Earth system interactions can affect the magnitude of the calculated effective radiative forcing.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal Rozenhaimer, Yohei Shinozuka, Connor Flynn, Amie Dobracki, Paquita Zuidema, Steven Howell, Steffen Freitag, and Sarah Doherty
Atmos. Meas. Tech., 14, 567–593, https://doi.org/10.5194/amt-14-567-2021, https://doi.org/10.5194/amt-14-567-2021, 2021
Short summary
Short summary
Based on observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS), this work establishes an observationally driven link from mid-visible aerosol optical depth (AOD) and other scene parameters to broadband shortwave irradiance (and by extension the direct aerosol radiative effect, DARE). The majority of the case-to-case DARE variability within the ORACLES dataset is attributable to the dependence on AOD and scene albedo.
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Wolfgang Stremme, Kimberly Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, https://doi.org/10.5194/amt-14-481-2021, 2021
Short summary
Short summary
This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
Robert G. Ryan, Jeremy D. Silver, Richard Querel, Dan Smale, Steve Rhodes, Matt Tully, Nicholas Jones, and Robyn Schofield
Atmos. Meas. Tech., 13, 6501–6519, https://doi.org/10.5194/amt-13-6501-2020, https://doi.org/10.5194/amt-13-6501-2020, 2020
Short summary
Short summary
Models have identified Australasia as a formaldehyde (HCHO) hotspot from vegetation sources, but few measurement studies exist to verify this. We compare, and find good agreement between, HCHO measurements using three – two ground-based and one satellite-based – different spectroscopic techniques in Australia and New Zealand. This gives confidence in using satellite observations to study HCHO and associated air chemistry and pollution problems in this under-studied part of the world.
Yang Wang, Arnoud Apituley, Alkiviadis Bais, Steffen Beirle, Nuria Benavent, Alexander Borovski, Ilya Bruchkouski, Ka Lok Chan, Sebastian Donner, Theano Drosoglou, Henning Finkenzeller, Martina M. Friedrich, Udo Frieß, David Garcia-Nieto, Laura Gómez-Martín, François Hendrick, Andreas Hilboll, Junli Jin, Paul Johnston, Theodore K. Koenig, Karin Kreher, Vinod Kumar, Aleksandra Kyuberis, Johannes Lampel, Cheng Liu, Haoran Liu, Jianzhong Ma, Oleg L. Polyansky, Oleg Postylyakov, Richard Querel, Alfonso Saiz-Lopez, Stefan Schmitt, Xin Tian, Jan-Lukas Tirpitz, Michel Van Roozendael, Rainer Volkamer, Zhuoru Wang, Pinhua Xie, Chengzhi Xing, Jin Xu, Margarita Yela, Chengxin Zhang, and Thomas Wagner
Atmos. Meas. Tech., 13, 5087–5116, https://doi.org/10.5194/amt-13-5087-2020, https://doi.org/10.5194/amt-13-5087-2020, 2020
Ilann Bourgeois, Jeff Peischl, Chelsea R. Thompson, Kenneth C. Aikin, Teresa Campos, Hannah Clark, Róisín Commane, Bruce Daube, Glenn W. Diskin, James W. Elkins, Ru-Shan Gao, Audrey Gaudel, Eric J. Hintsa, Bryan J. Johnson, Rigel Kivi, Kathryn McKain, Fred L. Moore, David D. Parrish, Richard Querel, Eric Ray, Ricardo Sánchez, Colm Sweeney, David W. Tarasick, Anne M. Thompson, Valérie Thouret, Jacquelyn C. Witte, Steve C. Wofsy, and Thomas B. Ryerson
Atmos. Chem. Phys., 20, 10611–10635, https://doi.org/10.5194/acp-20-10611-2020, https://doi.org/10.5194/acp-20-10611-2020, 2020
Vidya Varma, Olaf Morgenstern, Paul Field, Kalli Furtado, Jonny Williams, and Patrick Hyder
Atmos. Chem. Phys., 20, 7741–7751, https://doi.org/10.5194/acp-20-7741-2020, https://doi.org/10.5194/acp-20-7741-2020, 2020
Short summary
Short summary
The present generation of global climate models has an insufficiently reflected short-wave radiation, especially over the Southern Ocean. This leads to an excessive heating of the ocean surface in the model, creating sea surface temperature biases and subsequent problems with atmospheric dynamics. Misrepresentation of clouds could be attributed to this radiation bias; we try to address this issue by slowing the growth rate of ice crystals and improving the supercooled liquid clouds in the model.
Daniele Visioni, Giovanni Pitari, Vincenzo Rizi, Marco Iarlori, Irene Cionni, Ilaria Quaglia, Hideharu Akiyoshi, Slimane Bekki, Neal Butchart, Martin Chipperfield, Makoto Deushi, Sandip S. Dhomse, Rolando Garcia, Patrick Joeckel, Douglas Kinnison, Jean-François Lamarque, Marion Marchand, Martine Michou, Olaf Morgenstern, Tatsuya Nagashima, Fiona M. O'Connor, Luke D. Oman, David Plummer, Eugene Rozanov, David Saint-Martin, Robyn Schofield, John Scinocca, Andrea Stenke, Kane Stone, Kengo Sudo, Taichu Y. Tanaka, Simone Tilmes, Holger Tost, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-525, https://doi.org/10.5194/acp-2020-525, 2020
Preprint withdrawn
Short summary
Short summary
In this work we analyse the trend in ozone profiles taken at L'Aquila (Italy, 42.4° N) for seventeen years, between 2000 and 2016 and compare them against already available measured ozone trends. We try to understand and explain the observed trends at various heights in light of the simulations from seventeen different model, highlighting the contribution of changes in circulation and chemical ozone loss during this time period.
Marta Abalos, Clara Orbe, Douglas E. Kinnison, David Plummer, Luke D. Oman, Patrick Jöckel, Olaf Morgenstern, Rolando R. Garcia, Guang Zeng, Kane A. Stone, and Martin Dameris
Atmos. Chem. Phys., 20, 6883–6901, https://doi.org/10.5194/acp-20-6883-2020, https://doi.org/10.5194/acp-20-6883-2020, 2020
Short summary
Short summary
A set of state-of-the art chemistry–climate models is used to examine future changes in downward transport from the stratosphere, a key contributor to tropospheric ozone. The acceleration of the stratospheric circulation results in increased stratosphere-to-troposphere transport. In the subtropics, downward advection into the troposphere is enhanced due to climate change. At higher latitudes, the ozone reservoir above the tropopause is enlarged due to the stronger circulation and ozone recovery.
Peter Kuma, Adrian J. McDonald, Olaf Morgenstern, Simon P. Alexander, John J. Cassano, Sally Garrett, Jamie Halla, Sean Hartery, Mike J. Harvey, Simon Parsons, Graeme Plank, Vidya Varma, and Jonny Williams
Atmos. Chem. Phys., 20, 6607–6630, https://doi.org/10.5194/acp-20-6607-2020, https://doi.org/10.5194/acp-20-6607-2020, 2020
Short summary
Short summary
We evaluate clouds over the Southern Ocean in the climate model HadGEM3 and reanalysis MERRA-2 using ship-based ceilometer and radiosonde observations. We find the models underestimate cloud cover by 18–25 %, with clouds below 2 km dominant in reality but lacking in the models. We find a strong link between clouds, atmospheric stability and sea surface temperature in observations but not in the models, implying that sub-grid processes do not generate enough cloud in response to these conditions.
Karin Kreher, Michel Van Roozendael, Francois Hendrick, Arnoud Apituley, Ermioni Dimitropoulou, Udo Frieß, Andreas Richter, Thomas Wagner, Johannes Lampel, Nader Abuhassan, Li Ang, Monica Anguas, Alkis Bais, Nuria Benavent, Tim Bösch, Kristof Bognar, Alexander Borovski, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Henning Finkenzeller, David Garcia-Nieto, Clio Gielen, Laura Gómez-Martín, Nan Hao, Bas Henzing, Jay R. Herman, Christian Hermans, Syedul Hoque, Hitoshi Irie, Junli Jin, Paul Johnston, Junaid Khayyam Butt, Fahim Khokhar, Theodore K. Koenig, Jonas Kuhn, Vinod Kumar, Cheng Liu, Jianzhong Ma, Alexis Merlaud, Abhishek K. Mishra, Moritz Müller, Monica Navarro-Comas, Mareike Ostendorf, Andrea Pazmino, Enno Peters, Gaia Pinardi, Manuel Pinharanda, Ankie Piters, Ulrich Platt, Oleg Postylyakov, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Alfonso Saiz-Lopez, Anja Schönhardt, Stefan F. Schreier, André Seyler, Vinayak Sinha, Elena Spinei, Kimberly Strong, Frederik Tack, Xin Tian, Martin Tiefengraber, Jan-Lukas Tirpitz, Jeroen van Gent, Rainer Volkamer, Mihalis Vrekoussis, Shanshan Wang, Zhuoru Wang, Mark Wenig, Folkard Wittrock, Pinhua H. Xie, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 13, 2169–2208, https://doi.org/10.5194/amt-13-2169-2020, https://doi.org/10.5194/amt-13-2169-2020, 2020
Short summary
Short summary
In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants during an instrument intercomparison campaign (CINDI-2) at Cabauw, the Netherlands. Here we report on the outcome of this intercomparison exercise. The three major goals were to characterise the differences between the participating instruments, to define a robust methodology for performance assessment, and to contribute to the harmonisation of the measurement settings and retrieval methods.
M. Patrick McCormick, Liqiao Lei, Michael T. Hill, John Anderson, Richard Querel, and Wolfgang Steinbrecht
Atmos. Meas. Tech., 13, 1287–1297, https://doi.org/10.5194/amt-13-1287-2020, https://doi.org/10.5194/amt-13-1287-2020, 2020
Short summary
Short summary
We present a validation of O3 data from the SAGE III-ISS instrument using ground-based lidars and ozonesondes from Hohenpeißenberg and Lauder as well as O3 data from the ACE-FTS instrument. Average differences in the O3 concentration between SAGE III-ISS and the lidar and sonde observations are < 10 % over much of the lower and middle stratosphere. The ACE comparisons are < 5 % from 20 to 45 km. These results provide confidence in the SAGE III measurements of global stratospheric O3 profiles.
Alexander T. Archibald, Fiona M. O'Connor, Nathan Luke Abraham, Scott Archer-Nicholls, Martyn P. Chipperfield, Mohit Dalvi, Gerd A. Folberth, Fraser Dennison, Sandip S. Dhomse, Paul T. Griffiths, Catherine Hardacre, Alan J. Hewitt, Richard S. Hill, Colin E. Johnson, James Keeble, Marcus O. Köhler, Olaf Morgenstern, Jane P. Mulcahy, Carlos Ordóñez, Richard J. Pope, Steven T. Rumbold, Maria R. Russo, Nicholas H. Savage, Alistair Sellar, Marc Stringer, Steven T. Turnock, Oliver Wild, and Guang Zeng
Geosci. Model Dev., 13, 1223–1266, https://doi.org/10.5194/gmd-13-1223-2020, https://doi.org/10.5194/gmd-13-1223-2020, 2020
Short summary
Short summary
Here we present a description and evaluation of the UKCA stratosphere–troposphere chemistry scheme (StratTrop vn 1.0) implemented in the UK Earth System Model (UKESM1). UKCA StratTrop represents a substantial step forward compared to previous versions of UKCA. We show here that it is fully suited to the challenges of representing interactions in a coupled Earth system model and identify key areas and components for future development that will make it even better in the future.
Julie M. Nicely, Bryan N. Duncan, Thomas F. Hanisco, Glenn M. Wolfe, Ross J. Salawitch, Makoto Deushi, Amund S. Haslerud, Patrick Jöckel, Béatrice Josse, Douglas E. Kinnison, Andrew Klekociuk, Michael E. Manyin, Virginie Marécal, Olaf Morgenstern, Lee T. Murray, Gunnar Myhre, Luke D. Oman, Giovanni Pitari, Andrea Pozzer, Ilaria Quaglia, Laura E. Revell, Eugene Rozanov, Andrea Stenke, Kane Stone, Susan Strahan, Simone Tilmes, Holger Tost, Daniel M. Westervelt, and Guang Zeng
Atmos. Chem. Phys., 20, 1341–1361, https://doi.org/10.5194/acp-20-1341-2020, https://doi.org/10.5194/acp-20-1341-2020, 2020
Short summary
Short summary
Differences in methane lifetime among global models are large and poorly understood. We use a neural network method and simulations from the Chemistry Climate Model Initiative to quantify the factors influencing methane lifetime spread among models and variations over time. UV photolysis, tropospheric ozone, and nitrogen oxides drive large model differences, while the same factors plus specific humidity contribute to a decreasing trend in methane lifetime between 1980 and 2015.
Laura E. Revell, Stefanie Kremser, Sean Hartery, Mike Harvey, Jane P. Mulcahy, Jonny Williams, Olaf Morgenstern, Adrian J. McDonald, Vidya Varma, Leroy Bird, and Alex Schuddeboom
Atmos. Chem. Phys., 19, 15447–15466, https://doi.org/10.5194/acp-19-15447-2019, https://doi.org/10.5194/acp-19-15447-2019, 2019
Short summary
Short summary
Aerosols over the Southern Ocean consist primarily of sea salt and sulfate, yet are seasonally biased in our model. We test three sulfate chemistry schemes to investigate DMS oxidation, which forms sulfate aerosol. Simulated cloud droplet number concentrations improve using more complex sulfate chemistry. We also show that a new sea spray aerosol source function, developed from measurements made on a recent Southern Ocean research voyage, improves the model's simulation of aerosol optical depth.
Keith M. Hines, David H. Bromwich, Sheng-Hung Wang, Israel Silber, Johannes Verlinde, and Dan Lubin
Atmos. Chem. Phys., 19, 12431–12454, https://doi.org/10.5194/acp-19-12431-2019, https://doi.org/10.5194/acp-19-12431-2019, 2019
Short summary
Short summary
We explore how well clouds are represented in numerical weather prediction over Antarctica, a very difficult environment for field programs where few studies have been conducted. Fortunately, a 2015–2017 field program for West Antarctica supplied observations. We achieve promising results with newer, more advanced cloud schemes. We need to understand the role of clouds and precipitation in the maintenance of the Antarctic ice mass to understand and predict sea level change over the 21st century.
Andreas Chrysanthou, Amanda C. Maycock, Martyn P. Chipperfield, Sandip Dhomse, Hella Garny, Douglas Kinnison, Hideharu Akiyoshi, Makoto Deushi, Rolando R. Garcia, Patrick Jöckel, Oliver Kirner, Giovanni Pitari, David A. Plummer, Laura Revell, Eugene Rozanov, Andrea Stenke, Taichu Y. Tanaka, Daniele Visioni, and Yousuke Yamashita
Atmos. Chem. Phys., 19, 11559–11586, https://doi.org/10.5194/acp-19-11559-2019, https://doi.org/10.5194/acp-19-11559-2019, 2019
Short summary
Short summary
We perform the first multi-model comparison of the impact of nudged meteorology on the stratospheric residual circulation (RC) in chemistry–climate models. Nudging meteorology does not constrain the mean strength of RC compared to free-running simulations, and despite the lack of agreement in the mean circulation, nudging tightly constrains the inter-annual variability in the tropical upward mass flux in the lower stratosphere. In summary, nudging strongly affects the representation of RC.
Kévin Lamy, Thierry Portafaix, Béatrice Josse, Colette Brogniez, Sophie Godin-Beekmann, Hassan Bencherif, Laura Revell, Hideharu Akiyoshi, Slimane Bekki, Michaela I. Hegglin, Patrick Jöckel, Oliver Kirner, Ben Liley, Virginie Marecal, Olaf Morgenstern, Andrea Stenke, Guang Zeng, N. Luke Abraham, Alexander T. Archibald, Neil Butchart, Martyn P. Chipperfield, Glauco Di Genova, Makoto Deushi, Sandip S. Dhomse, Rong-Ming Hu, Douglas Kinnison, Michael Kotkamp, Richard McKenzie, Martine Michou, Fiona M. O'Connor, Luke D. Oman, Giovanni Pitari, David A. Plummer, John A. Pyle, Eugene Rozanov, David Saint-Martin, Kengo Sudo, Taichu Y. Tanaka, Daniele Visioni, and Kohei Yoshida
Atmos. Chem. Phys., 19, 10087–10110, https://doi.org/10.5194/acp-19-10087-2019, https://doi.org/10.5194/acp-19-10087-2019, 2019
Short summary
Short summary
In this study, we simulate the ultraviolet radiation evolution during the 21st century on Earth's surface using the output from several numerical models which participated in the Chemistry-Climate Model Initiative. We present four possible futures which depend on greenhouse gases emissions. The role of ozone-depleting substances, greenhouse gases and aerosols are investigated. Our results emphasize the important role of aerosols for future ultraviolet radiation in the Northern Hemisphere.
Ohad Harari, Chaim I. Garfinkel, Shlomi Ziskin Ziv, Olaf Morgenstern, Guang Zeng, Simone Tilmes, Douglas Kinnison, Makoto Deushi, Patrick Jöckel, Andrea Pozzer, Fiona M. O'Connor, and Sean Davis
Atmos. Chem. Phys., 19, 9253–9268, https://doi.org/10.5194/acp-19-9253-2019, https://doi.org/10.5194/acp-19-9253-2019, 2019
Short summary
Short summary
Ozone depletion in the Antarctic has been shown to influence surface conditions, but the effects of ozone depletion in the Arctic on surface climate are unclear. We show that Arctic ozone does influence surface climate in both polar regions and tropical regions, though the proximate cause of these surface impacts is not yet clear.
Petr Šácha, Roland Eichinger, Hella Garny, Petr Pišoft, Simone Dietmüller, Laura de la Torre, David A. Plummer, Patrick Jöckel, Olaf Morgenstern, Guang Zeng, Neal Butchart, and Juan A. Añel
Atmos. Chem. Phys., 19, 7627–7647, https://doi.org/10.5194/acp-19-7627-2019, https://doi.org/10.5194/acp-19-7627-2019, 2019
Short summary
Short summary
Climate models robustly project a Brewer–Dobson circulation (BDC) acceleration in the course of climate change. Analyzing mean age of stratospheric air (AoA) from a subset of climate projection simulations, we find a remarkable agreement in simulating the largest AoA trends in the extratropical stratosphere. This is shown to be related with the upward shift of the circulation, resulting in a so-called stratospheric shrinkage, which could be one of the so-far-omitted BDC acceleration drivers.
Huang Yang, Darryn W. Waugh, Clara Orbe, Guang Zeng, Olaf Morgenstern, Douglas E. Kinnison, Jean-Francois Lamarque, Simone Tilmes, David A. Plummer, Patrick Jöckel, Susan E. Strahan, Kane A. Stone, and Robyn Schofield
Atmos. Chem. Phys., 19, 5511–5528, https://doi.org/10.5194/acp-19-5511-2019, https://doi.org/10.5194/acp-19-5511-2019, 2019
Short summary
Short summary
We evaluate the performance of a suite of models in simulating the large-scale transport from the northern midlatitudes to the Arctic using a CO-like idealized tracer. We find a large multi-model spread of the Arctic concentration of this CO-like tracer that is well correlated with the differences in the location of the midlatitude jet as well as the northern Hadley Cell edge. Our results suggest the Hadley Cell is key and zonal-mean transport by surface meridional flow needs better constraint.
Fraser Dennison, James Keeble, Olaf Morgenstern, Guang Zeng, N. Luke Abraham, and Xin Yang
Geosci. Model Dev., 12, 1227–1239, https://doi.org/10.5194/gmd-12-1227-2019, https://doi.org/10.5194/gmd-12-1227-2019, 2019
Short summary
Short summary
Two developments are made to the United Kingdom Chemistry and Aerosols (UKCA) model to improve simulation of stratospheric ozone. The first is the addition of a solar cycle. The influence on ozone from the solar cycle is found to be 1–2 %, which is consistent with other studies. The second is to the heterogeneous chemistry, the most significant change being the addition of reactions involving bromine species. This was shown to reduce ozone biases relative to observations in most regions.
Roland Eichinger, Simone Dietmüller, Hella Garny, Petr Šácha, Thomas Birner, Harald Bönisch, Giovanni Pitari, Daniele Visioni, Andrea Stenke, Eugene Rozanov, Laura Revell, David A. Plummer, Patrick Jöckel, Luke Oman, Makoto Deushi, Douglas E. Kinnison, Rolando Garcia, Olaf Morgenstern, Guang Zeng, Kane Adam Stone, and Robyn Schofield
Atmos. Chem. Phys., 19, 921–940, https://doi.org/10.5194/acp-19-921-2019, https://doi.org/10.5194/acp-19-921-2019, 2019
Short summary
Short summary
To shed more light upon the changes in stratospheric circulation in the 21st century, climate projection simulations of 10 state-of-the-art global climate models, spanning from 1960 to 2100, are analyzed. The study shows that in addition to changes in transport, mixing also plays an important role in stratospheric circulation and that the properties of mixing vary over time. Furthermore, the influence of mixing is quantified and a dynamical framework is provided to understand the changes.
Jordis S. Tradowsky, Gregory E. Bodeker, Richard R. Querel, Peter J. H. Builtjes, and Jürgen Fischer
Earth Syst. Sci. Data, 10, 2195–2211, https://doi.org/10.5194/essd-10-2195-2018, https://doi.org/10.5194/essd-10-2195-2018, 2018
Short summary
Short summary
A best-estimate data set of the temperature profile above the atmospheric measurement facility at Lauder, New Zealand, has been developed. This site atmospheric state best estimate (SASBE) combines atmospheric measurements made at two locations and includes an estimate of uncertainty on every data point. The SASBE enhances the value of measurements made by a reference-quality climate observing network and may be used for a variety of purposes in research and education.
Laura E. Revell, Andrea Stenke, Fiona Tummon, Aryeh Feinberg, Eugene Rozanov, Thomas Peter, N. Luke Abraham, Hideharu Akiyoshi, Alexander T. Archibald, Neal Butchart, Makoto Deushi, Patrick Jöckel, Douglas Kinnison, Martine Michou, Olaf Morgenstern, Fiona M. O'Connor, Luke D. Oman, Giovanni Pitari, David A. Plummer, Robyn Schofield, Kane Stone, Simone Tilmes, Daniele Visioni, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys., 18, 16155–16172, https://doi.org/10.5194/acp-18-16155-2018, https://doi.org/10.5194/acp-18-16155-2018, 2018
Short summary
Short summary
Global models such as those participating in the Chemistry-Climate Model Initiative (CCMI) consistently simulate biases in tropospheric ozone compared with observations. We performed an advanced statistical analysis with one of the CCMI models to understand the cause of the bias. We found that emissions of ozone precursor gases are the dominant driver of the bias, implying either that the emissions are too large, or that the way in which the model handles emissions needs to be improved.
Blanca Ayarzagüena, Lorenzo M. Polvani, Ulrike Langematz, Hideharu Akiyoshi, Slimane Bekki, Neal Butchart, Martin Dameris, Makoto Deushi, Steven C. Hardiman, Patrick Jöckel, Andrew Klekociuk, Marion Marchand, Martine Michou, Olaf Morgenstern, Fiona M. O'Connor, Luke D. Oman, David A. Plummer, Laura Revell, Eugene Rozanov, David Saint-Martin, John Scinocca, Andrea Stenke, Kane Stone, Yousuke Yamashita, Kohei Yoshida, and Guang Zeng
Atmos. Chem. Phys., 18, 11277–11287, https://doi.org/10.5194/acp-18-11277-2018, https://doi.org/10.5194/acp-18-11277-2018, 2018
Short summary
Short summary
Stratospheric sudden warmings (SSWs) are natural major disruptions of the polar stratospheric circulation that also affect surface weather. In the literature there are conflicting claims as to whether SSWs will change in the future. The confusion comes from studies using different models and methods. Here we settle the question by analysing 12 models with a consistent methodology, to show that no robust changes in frequency and other features are expected over the 21st century.
Ben Jolly, Peter Kuma, Adrian McDonald, and Simon Parsons
Atmos. Chem. Phys., 18, 9723–9739, https://doi.org/10.5194/acp-18-9723-2018, https://doi.org/10.5194/acp-18-9723-2018, 2018
Short summary
Short summary
Clouds in the Ross Sea and Ross Ice Shelf regions are examined using a combination of satellite observations from the CloudSat and CALIPSO satellite datasets. We show that previous studies may have included an artefact at high altitudes which under-estimated cloud occurrence. We also find that the meteorological regime is a stronger control of cloud occurrence, cloud type and cloud top than season over this region, though season is a strong control on the phase of cloud.
Sandip S. Dhomse, Douglas Kinnison, Martyn P. Chipperfield, Ross J. Salawitch, Irene Cionni, Michaela I. Hegglin, N. Luke Abraham, Hideharu Akiyoshi, Alex T. Archibald, Ewa M. Bednarz, Slimane Bekki, Peter Braesicke, Neal Butchart, Martin Dameris, Makoto Deushi, Stacey Frith, Steven C. Hardiman, Birgit Hassler, Larry W. Horowitz, Rong-Ming Hu, Patrick Jöckel, Beatrice Josse, Oliver Kirner, Stefanie Kremser, Ulrike Langematz, Jared Lewis, Marion Marchand, Meiyun Lin, Eva Mancini, Virginie Marécal, Martine Michou, Olaf Morgenstern, Fiona M. O'Connor, Luke Oman, Giovanni Pitari, David A. Plummer, John A. Pyle, Laura E. Revell, Eugene Rozanov, Robyn Schofield, Andrea Stenke, Kane Stone, Kengo Sudo, Simone Tilmes, Daniele Visioni, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys., 18, 8409–8438, https://doi.org/10.5194/acp-18-8409-2018, https://doi.org/10.5194/acp-18-8409-2018, 2018
Short summary
Short summary
We analyse simulations from the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion by anthropogenic chlorine and bromine. The simulations from 20 models project that global column ozone will return to 1980 values in 2047 (uncertainty range 2042–2052). Return dates in other regions vary depending on factors related to climate change and importance of chlorine and bromine. Column ozone in the tropics may continue to decline.
Clara Orbe, Huang Yang, Darryn W. Waugh, Guang Zeng, Olaf Morgenstern, Douglas E. Kinnison, Jean-Francois Lamarque, Simone Tilmes, David A. Plummer, John F. Scinocca, Beatrice Josse, Virginie Marecal, Patrick Jöckel, Luke D. Oman, Susan E. Strahan, Makoto Deushi, Taichu Y. Tanaka, Kohei Yoshida, Hideharu Akiyoshi, Yousuke Yamashita, Andreas Stenke, Laura Revell, Timofei Sukhodolov, Eugene Rozanov, Giovanni Pitari, Daniele Visioni, Kane A. Stone, Robyn Schofield, and Antara Banerjee
Atmos. Chem. Phys., 18, 7217–7235, https://doi.org/10.5194/acp-18-7217-2018, https://doi.org/10.5194/acp-18-7217-2018, 2018
Short summary
Short summary
In this study we compare a few atmospheric transport properties among several numerical models that are used to study the influence of atmospheric chemistry on climate. We show that there are large differences among models in terms of the timescales that connect the Northern Hemisphere midlatitudes, where greenhouse gases and ozone-depleting substances are emitted, to the Southern Hemisphere. Our results may have important implications for how models represent atmospheric composition.
Simone Dietmüller, Roland Eichinger, Hella Garny, Thomas Birner, Harald Boenisch, Giovanni Pitari, Eva Mancini, Daniele Visioni, Andrea Stenke, Laura Revell, Eugene Rozanov, David A. Plummer, John Scinocca, Patrick Jöckel, Luke Oman, Makoto Deushi, Shibata Kiyotaka, Douglas E. Kinnison, Rolando Garcia, Olaf Morgenstern, Guang Zeng, Kane Adam Stone, and Robyn Schofield
Atmos. Chem. Phys., 18, 6699–6720, https://doi.org/10.5194/acp-18-6699-2018, https://doi.org/10.5194/acp-18-6699-2018, 2018
Olaf Morgenstern, Kane A. Stone, Robyn Schofield, Hideharu Akiyoshi, Yousuke Yamashita, Douglas E. Kinnison, Rolando R. Garcia, Kengo Sudo, David A. Plummer, John Scinocca, Luke D. Oman, Michael E. Manyin, Guang Zeng, Eugene Rozanov, Andrea Stenke, Laura E. Revell, Giovanni Pitari, Eva Mancini, Glauco Di Genova, Daniele Visioni, Sandip S. Dhomse, and Martyn P. Chipperfield
Atmos. Chem. Phys., 18, 1091–1114, https://doi.org/10.5194/acp-18-1091-2018, https://doi.org/10.5194/acp-18-1091-2018, 2018
Short summary
Short summary
We assess how ozone as simulated by a group of chemistry–climate models responds to variations in man-made climate gases and ozone-depleting substances. We find some agreement, particularly in the middle and upper stratosphere, but also considerable disagreement elsewhere. Such disagreement affects the reliability of future ozone projections based on these models, and also constitutes a source of uncertainty in climate projections using prescribed ozone derived from these simulations.
Fraser Dennison, Adrian McDonald, and Olaf Morgenstern
Atmos. Chem. Phys., 17, 14075–14084, https://doi.org/10.5194/acp-17-14075-2017, https://doi.org/10.5194/acp-17-14075-2017, 2017
Short summary
Short summary
The Antarctic ozone is not centred directly over the pole. In this research we examine how the position and shape of the ozone hole changes using a chemistry–climate model. As ozone becomes increasingly depleted during the late 20th century the centre of the ozone hole moves toward the west and becomes more circular. As the ozone hole recovers over the course of the 21st century the ozone hole moves back towards the east.
Travis N. Knepp, Richard Querel, Paul Johnston, Larry Thomason, David Flittner, and Joseph M. Zawodny
Atmos. Meas. Tech., 10, 4363–4372, https://doi.org/10.5194/amt-10-4363-2017, https://doi.org/10.5194/amt-10-4363-2017, 2017
Short summary
Short summary
The SAGE-III instrument was launched in February 2017. As with any new instrument, a significant post-launch activity is planned to validate the data products. Validation of trace gases with short photolytic lifetimes is challenging, though careful use of Pandora-type instruments may prove beneficial. A careful intercomparison of Pandora and NIWA's M07 instrument was carried out. Results show Pandora to be well correlated with M07, showing its viability as a validation tool for SAGE science.
Wolfgang Steinbrecht, Lucien Froidevaux, Ryan Fuller, Ray Wang, John Anderson, Chris Roth, Adam Bourassa, Doug Degenstein, Robert Damadeo, Joe Zawodny, Stacey Frith, Richard McPeters, Pawan Bhartia, Jeannette Wild, Craig Long, Sean Davis, Karen Rosenlof, Viktoria Sofieva, Kaley Walker, Nabiz Rahpoe, Alexei Rozanov, Mark Weber, Alexandra Laeng, Thomas von Clarmann, Gabriele Stiller, Natalya Kramarova, Sophie Godin-Beekmann, Thierry Leblanc, Richard Querel, Daan Swart, Ian Boyd, Klemens Hocke, Niklaus Kämpfer, Eliane Maillard Barras, Lorena Moreira, Gerald Nedoluha, Corinne Vigouroux, Thomas Blumenstock, Matthias Schneider, Omaira García, Nicholas Jones, Emmanuel Mahieu, Dan Smale, Michael Kotkamp, John Robinson, Irina Petropavlovskikh, Neil Harris, Birgit Hassler, Daan Hubert, and Fiona Tummon
Atmos. Chem. Phys., 17, 10675–10690, https://doi.org/10.5194/acp-17-10675-2017, https://doi.org/10.5194/acp-17-10675-2017, 2017
Short summary
Short summary
Thanks to the 1987 Montreal Protocol and its amendments, ozone-depleting chlorine (and bromine) in the stratosphere has declined slowly since the late 1990s. Improved and extended long-term ozone profile observations from satellites and ground-based stations confirm that ozone is responding as expected and has increased by about 2 % per decade since 2000 in the upper stratosphere, around 40 km altitude. At lower altitudes, however, ozone has not changed significantly since 2000.
Guang Zeng, Olaf Morgenstern, Hisako Shiona, Alan J. Thomas, Richard R. Querel, and Sylvia E. Nichol
Atmos. Chem. Phys., 17, 10495–10513, https://doi.org/10.5194/acp-17-10495-2017, https://doi.org/10.5194/acp-17-10495-2017, 2017
Short summary
Short summary
The long-term ozonesonde record from Lauder, New Zealand, which covers 1987 to 2014, shows a significant positive trend in lower tropospheric ozone, and a significant negative trend in the tropopause region. We conduct a statistical and chemistry–climate model analysis to identify the causes of these trends. We attribute these trends to anthropogenic influences and large-scale dynamical effects such as increasing tropopause height and an increase in stratosphere–troposphere exchange.
Guanyu Huang, Xiong Liu, Kelly Chance, Kai Yang, Pawan K. Bhartia, Zhaonan Cai, Marc Allaart, Gérard Ancellet, Bertrand Calpini, Gerrie J. R. Coetzee, Emilio Cuevas-Agulló, Manuel Cupeiro, Hugo De Backer, Manvendra K. Dubey, Henry E. Fuelberg, Masatomo Fujiwara, Sophie Godin-Beekmann, Tristan J. Hall, Bryan Johnson, Everette Joseph, Rigel Kivi, Bogumil Kois, Ninong Komala, Gert König-Langlo, Giovanni Laneve, Thierry Leblanc, Marion Marchand, Kenneth R. Minschwaner, Gary Morris, Michael J. Newchurch, Shin-Ya Ogino, Nozomu Ohkawara, Ankie J. M. Piters, Françoise Posny, Richard Querel, Rinus Scheele, Frank J. Schmidlin, Russell C. Schnell, Otto Schrems, Henry Selkirk, Masato Shiotani, Pavla Skrivánková, René Stübi, Ghassan Taha, David W. Tarasick, Anne M. Thompson, Valérie Thouret, Matthew B. Tully, Roeland Van Malderen, Holger Vömel, Peter von der Gathen, Jacquelyn C. Witte, and Margarita Yela
Atmos. Meas. Tech., 10, 2455–2475, https://doi.org/10.5194/amt-10-2455-2017, https://doi.org/10.5194/amt-10-2455-2017, 2017
Short summary
Short summary
It is essential to understand the data quality of +10-year OMI ozone product and impacts of the “row anomaly” (RA). We validate the OMI Ozone Profile (PROFOZ) product from Oct 2004 to Dec 2014 against ozonesonde observations globally. Generally, OMI has good agreement with ozonesondes. The spatiotemporal variation of retrieval performance suggests the need to improve OMI’s radiometric calibration especially during the post-RA period to maintain the long-term stability.
Kevin M. Smalley, Andrew E. Dessler, Slimane Bekki, Makoto Deushi, Marion Marchand, Olaf Morgenstern, David A. Plummer, Kiyotaka Shibata, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys., 17, 8031–8044, https://doi.org/10.5194/acp-17-8031-2017, https://doi.org/10.5194/acp-17-8031-2017, 2017
Short summary
Short summary
This paper explains a new way to evaluate simulated lower-stratospheric water vapor. We use a multivariate linear regression to predict 21st century lower stratospheric water vapor within 12 chemistry climate models using tropospheric warming, the Brewer–Dobson circulation, and the quasi-biennial oscillation as predictors. This methodology produce strong fits to simulated water vapor, and potentially represents a superior method to evaluate model trends in lower-stratospheric water vapor.
Enno Peters, Gaia Pinardi, André Seyler, Andreas Richter, Folkard Wittrock, Tim Bösch, Michel Van Roozendael, François Hendrick, Theano Drosoglou, Alkiviadis F. Bais, Yugo Kanaya, Xiaoyi Zhao, Kimberly Strong, Johannes Lampel, Rainer Volkamer, Theodore Koenig, Ivan Ortega, Olga Puentedura, Mónica Navarro-Comas, Laura Gómez, Margarita Yela González, Ankie Piters, Julia Remmers, Yang Wang, Thomas Wagner, Shanshan Wang, Alfonso Saiz-Lopez, David García-Nieto, Carlos A. Cuevas, Nuria Benavent, Richard Querel, Paul Johnston, Oleg Postylyakov, Alexander Borovski, Alexander Elokhov, Ilya Bruchkouski, Haoran Liu, Cheng Liu, Qianqian Hong, Claudia Rivera, Michel Grutter, Wolfgang Stremme, M. Fahim Khokhar, Junaid Khayyam, and John P. Burrows
Atmos. Meas. Tech., 10, 955–978, https://doi.org/10.5194/amt-10-955-2017, https://doi.org/10.5194/amt-10-955-2017, 2017
Short summary
Short summary
This work is about harmonization of differential optical absorption spectroscopy retrieval codes, which is a remote sensing technique widely used to derive atmospheric trace gas amounts. The study is based on ground-based measurements performed during the Multi-Axis DOAS Comparison campaign for Aerosols and Trace gases (MAD-CAT) in Mainz, Germany, in summer 2013. In total, 17 international groups working in the field of the DOAS technique participated in this study.
Olaf Morgenstern, Michaela I. Hegglin, Eugene Rozanov, Fiona M. O'Connor, N. Luke Abraham, Hideharu Akiyoshi, Alexander T. Archibald, Slimane Bekki, Neal Butchart, Martyn P. Chipperfield, Makoto Deushi, Sandip S. Dhomse, Rolando R. Garcia, Steven C. Hardiman, Larry W. Horowitz, Patrick Jöckel, Beatrice Josse, Douglas Kinnison, Meiyun Lin, Eva Mancini, Michael E. Manyin, Marion Marchand, Virginie Marécal, Martine Michou, Luke D. Oman, Giovanni Pitari, David A. Plummer, Laura E. Revell, David Saint-Martin, Robyn Schofield, Andrea Stenke, Kane Stone, Kengo Sudo, Taichu Y. Tanaka, Simone Tilmes, Yousuke Yamashita, Kohei Yoshida, and Guang Zeng
Geosci. Model Dev., 10, 639–671, https://doi.org/10.5194/gmd-10-639-2017, https://doi.org/10.5194/gmd-10-639-2017, 2017
Short summary
Short summary
We present a review of the make-up of 20 models participating in the Chemistry–Climate Model Initiative (CCMI). In comparison to earlier such activities, most of these models comprise a whole-atmosphere chemistry, and several of them include an interactive ocean module. This makes them suitable for studying the interactions of tropospheric air quality, stratospheric ozone, and climate. The paper lays the foundation for other studies using the CCMI simulations for scientific analysis.
Ethan R. Dale, Adrian J. McDonald, Jack H. J. Coggins, and Wolfgang Rack
The Cryosphere, 11, 267–280, https://doi.org/10.5194/tc-11-267-2017, https://doi.org/10.5194/tc-11-267-2017, 2017
Short summary
Short summary
This work studies the affects of strong winds on sea ice within the Ross Sea polynya. We compare both automatic weather station (AWS) and reanalysis wind data with sea ice concentration (SIC) measurements based on satellite images. Due to its low resolution, the reanalysis data were unable to reproduce several relationships found between the AWS and SIC data. We find that the strongest third of wind speeds had the most significant affect on SIC and resulting sea ice production.
Leon S. Friedrich, Adrian J. McDonald, Gregory E. Bodeker, Kathy E. Cooper, Jared Lewis, and Alexander J. Paterson
Atmos. Chem. Phys., 17, 855–866, https://doi.org/10.5194/acp-17-855-2017, https://doi.org/10.5194/acp-17-855-2017, 2017
Short summary
Short summary
Information from long-duration balloons flying in the Southern Hemisphere stratosphere during 2014 as part of X Project Loon are used to assess the quality of a number of different reanalyses. This work assesses the potential of the X Project Loon observations to validate outputs from the reanalysis models. In particular, we examined how the model winds compared with those derived from the balloon GPS information. We also examined simulated trajectories compared with the true trajectories.
Laura López-Comí, Olaf Morgenstern, Guang Zeng, Sarah L. Masters, Richard R. Querel, and Gerald E. Nedoluha
Atmos. Chem. Phys., 16, 14599–14619, https://doi.org/10.5194/acp-16-14599-2016, https://doi.org/10.5194/acp-16-14599-2016, 2016
Short summary
Short summary
The hydroxyl radical (OH) is known for removing various pollutants from the atmosphere. Chemistry–climate models disagree on how much OH is found in the atmosphere. Here we use a single column model, set up for Lauder (New Zealand), to assess how OH responds to correcting model biases in long-lived constituents and temperature. We find some considerable sensitivity to correcting water vapour and ozone, with lesser contributions due to correcting methane, carbon monoxide, and temperature.
Daan Hubert, Jean-Christopher Lambert, Tijl Verhoelst, José Granville, Arno Keppens, Jean-Luc Baray, Adam E. Bourassa, Ugo Cortesi, Doug A. Degenstein, Lucien Froidevaux, Sophie Godin-Beekmann, Karl W. Hoppel, Bryan J. Johnson, Erkki Kyrölä, Thierry Leblanc, Günter Lichtenberg, Marion Marchand, C. Thomas McElroy, Donal Murtagh, Hideaki Nakane, Thierry Portafaix, Richard Querel, James M. Russell III, Jacobo Salvador, Herman G. J. Smit, Kerstin Stebel, Wolfgang Steinbrecht, Kevin B. Strawbridge, René Stübi, Daan P. J. Swart, Ghassan Taha, David W. Tarasick, Anne M. Thompson, Joachim Urban, Joanna A. E. van Gijsel, Roeland Van Malderen, Peter von der Gathen, Kaley A. Walker, Elian Wolfram, and Joseph M. Zawodny
Atmos. Meas. Tech., 9, 2497–2534, https://doi.org/10.5194/amt-9-2497-2016, https://doi.org/10.5194/amt-9-2497-2016, 2016
Short summary
Short summary
A more detailed understanding of satellite O3 profile data records is vital for further progress in O3 research. To this end, we made a comprehensive assessment of 14 limb/occultation profilers using ground-based reference data. The mutual consistency of satellite O3 in terms of bias, short-term variability and decadal stability is generally good over most of the stratosphere. However, we identified some exceptions that impact the quality of recently merged data sets and ozone trend assessments.
Israel Silber, Colin Price, and Craig J. Rodger
Atmos. Chem. Phys., 16, 3279–3288, https://doi.org/10.5194/acp-16-3279-2016, https://doi.org/10.5194/acp-16-3279-2016, 2016
Short summary
Short summary
We report for the first time that the semi-annual oscillation (SAO) is one of the dominant oscillations in the nighttime lower ionosphere, using ground-based measurements of VLF signals reflected off the lower part of the ionosphere. We conclude that the origins of this oscillation are oscillatory changes of the D region's electrical characteristics, driven by NOx transport from the lower thermosphere. This oscillation should be considered in lower ionospheric and VLF wave propagation models.
Kane A. Stone, Olaf Morgenstern, David J. Karoly, Andrew R. Klekociuk, W. John French, N. Luke Abraham, and Robyn Schofield
Atmos. Chem. Phys., 16, 2401–2415, https://doi.org/10.5194/acp-16-2401-2016, https://doi.org/10.5194/acp-16-2401-2016, 2016
Short summary
Short summary
This paper describes the set-up and evaluation of the Australian Community Climate and Earth System Simulator – chemistry-climate model.
Emphasis is placed on the Antarctic ozone hole, which is very important considering its role modulating Southern Hemisphere surface climate. While the model simulates the global distribution of ozone well, there is a disparity in the vertical location of springtime ozone depletion over Antarctica, highlighting important areas for future development.
Emphasis is placed on the Antarctic ozone hole, which is very important considering its role modulating Southern Hemisphere surface climate. While the model simulates the global distribution of ozone well, there is a disparity in the vertical location of springtime ozone depletion over Antarctica, highlighting important areas for future development.
T. Ning, J. Wang, G. Elgered, G. Dick, J. Wickert, M. Bradke, M. Sommer, R. Querel, and D. Smale
Atmos. Meas. Tech., 9, 79–92, https://doi.org/10.5194/amt-9-79-2016, https://doi.org/10.5194/amt-9-79-2016, 2016
Short summary
Short summary
Integrated water vapour (IWV) obtained from GNSS is to be developed into a GRUAN data product. In addition to the actual measurement, this data product needs to provide an estimate of the measurement uncertainty at the same time resolution as the actual measurement. The method developed in the paper fulfils the requirement by assigning a specific uncertainty to each data point. The method is also valuable for all applications of GNSS IWV data in atmospheric research and weather forecast.
N. R. P. Harris, B. Hassler, F. Tummon, G. E. Bodeker, D. Hubert, I. Petropavlovskikh, W. Steinbrecht, J. Anderson, P. K. Bhartia, C. D. Boone, A. Bourassa, S. M. Davis, D. Degenstein, A. Delcloo, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, N. Jones, M. J. Kurylo, E. Kyrölä, M. Laine, S. T. Leblanc, J.-C. Lambert, B. Liley, E. Mahieu, A. Maycock, M. de Mazière, A. Parrish, R. Querel, K. H. Rosenlof, C. Roth, C. Sioris, J. Staehelin, R. S. Stolarski, R. Stübi, J. Tamminen, C. Vigouroux, K. A. Walker, H. J. Wang, J. Wild, and J. M. Zawodny
Atmos. Chem. Phys., 15, 9965–9982, https://doi.org/10.5194/acp-15-9965-2015, https://doi.org/10.5194/acp-15-9965-2015, 2015
Short summary
Short summary
Trends in the vertical distribution of ozone are reported for new and recently revised data sets. The amount of ozone-depleting compounds in the stratosphere peaked in the second half of the 1990s. We examine the trends before and after that peak to see if any change in trend is discernible. The previously reported decreases are confirmed. Furthermore, the downward trend in upper stratospheric ozone has not continued. The possible significance of any increase is discussed in detail.
G. Zeng, J. E. Williams, J. A. Fisher, L. K. Emmons, N. B. Jones, O. Morgenstern, J. Robinson, D. Smale, C. Paton-Walsh, and D. W. T. Griffith
Atmos. Chem. Phys., 15, 7217–7245, https://doi.org/10.5194/acp-15-7217-2015, https://doi.org/10.5194/acp-15-7217-2015, 2015
Short summary
Short summary
We assess the impact of biogenic emissions on CO and HCHO in the Southern Hemisphere (SH), with simulations using different emission inventories. Differences in biogenic emissions result in large differences on modelled CO in the source and the remote regions. Substantial inter-model differences exist. Models significantly underestimate observed HCHO columns in the SH, suggesting missing sources in the models. Differences in the CO/OH/CH4 chemistry lead to differences in HCHO in remote regions.
G. E. Nedoluha, I. S. Boyd, A. Parrish, R. M. Gomez, D. R. Allen, L. Froidevaux, B. J. Connor, and R. R. Querel
Atmos. Chem. Phys., 15, 6817–6826, https://doi.org/10.5194/acp-15-6817-2015, https://doi.org/10.5194/acp-15-6817-2015, 2015
Short summary
Short summary
This paper highlights 2 unusual mid-stratospheric O3 anomalies in our 22-year ground-based data set. One of these is a large month long increase in June 2001 which we are able to associate with very unusually low equatorial air which persists over Lauder for much of June. The other O3 anomaly persists for ~4 years; using MLS data, we show that this is associated with unusually high N2O during this period. During this period there is also a low O3 and N2O anomaly in the tropics.
S. S. Dhomse, K. M. Emmerson, G. W. Mann, N. Bellouin, K. S. Carslaw, M. P. Chipperfield, R. Hommel, N. L. Abraham, P. Telford, P. Braesicke, M. Dalvi, C. E. Johnson, F. O'Connor, O. Morgenstern, J. A. Pyle, T. Deshler, J. M. Zawodny, and L. W. Thomason
Atmos. Chem. Phys., 14, 11221–11246, https://doi.org/10.5194/acp-14-11221-2014, https://doi.org/10.5194/acp-14-11221-2014, 2014
F. M. O'Connor, C. E. Johnson, O. Morgenstern, N. L. Abraham, P. Braesicke, M. Dalvi, G. A. Folberth, M. G. Sanderson, P. J. Telford, A. Voulgarakis, P. J. Young, G. Zeng, W. J. Collins, and J. A. Pyle
Geosci. Model Dev., 7, 41–91, https://doi.org/10.5194/gmd-7-41-2014, https://doi.org/10.5194/gmd-7-41-2014, 2014
P. E. Huck, G. E. Bodeker, S. Kremser, A. J. McDonald, M. Rex, and H. Struthers
Atmos. Chem. Phys., 13, 3237–3243, https://doi.org/10.5194/acp-13-3237-2013, https://doi.org/10.5194/acp-13-3237-2013, 2013
P. J. Telford, N. L. Abraham, A. T. Archibald, P. Braesicke, M. Dalvi, O. Morgenstern, F. M. O'Connor, N. A. D. Richards, and J. A. Pyle
Geosci. Model Dev., 6, 161–177, https://doi.org/10.5194/gmd-6-161-2013, https://doi.org/10.5194/gmd-6-161-2013, 2013
Related subject area
Atmospheric sciences
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
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
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
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
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
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
Short summary
Short summary
This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
Short summary
Short summary
This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
Short summary
Short summary
We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
Short summary
Short summary
Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
Short summary
Short summary
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, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Cited articles
Baars, H., Kanitz, T., Engelmann, R., Althausen, D., Heese, B., Komppula, M., Preißler, J., Tesche, M., Ansmann, A., Wandinger, U., Lim, J.-H., Ahn, J. Y., Stachlewska, I. S., Amiridis, V., Marinou, E., Seifert, P., Hofer, J., Skupin, A., Schneider, F., Bohlmann, S., Foth, A., Bley, S., Pfüller, A., Giannakaki, E., Lihavainen, H., Viisanen, Y., Hooda, R. K., Pereira, S. N., Bortoli, D., Wagner, F., Mattis, I., Janicka, L., Markowicz, K. M., Achtert, P., Artaxo, P., Pauliquevis, T., Souza, R. A. F., Sharma, V. P., van Zyl, P. G., Beukes, J. P., Sun, J., Rohwer, E. G., Deng, R., Mamouri, R.-E., and Zamorano, F.: An overview of the first decade of PollyNET: an emerging network of automated Raman-polarization lidars for continuous aerosol profiling, Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016, 2016. a
Baran, A. J.: A review of the light scattering properties of cirrus, J.
Quant. Spectrosc. Ra., 110, 1239–1260,
https://doi.org/10.1016/j.jqsrt.2009.02.026, 2009. a
Bastin, S., Chiriaco, M., and Drobinski, P.: Control of radiation and
evaporation on temperature variability in a WRF regional climate simulation:
comparison with colocated long term ground based observations near Paris,
Clim. Dynam., 51, 985–1003, https://doi.org/10.1007/s00382-016-2974-1, 2018. a
Bi, L., Yang, P., Kattawar, G. W., Baum, B. A., Hu, Y. X., Winker, D. M.,
Brock, R. S., and Lu, J. Q.: Simulation of the color ratio associated with
the backscattering of radiation by ice particles at the wavelengths of 0.532
and 1.064 µm, J. Geophys. Res., 114, D00H08,
https://doi.org/10.1029/2009jd011759, 2009. 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
Borovoi, A., Konoshonkin, A., and Kustova, N.: Backscatter ratios for arbitrary
oriented hexagonal ice crystals of cirrus clouds, Opt. Lett., 39, 5788–5791,
https://doi.org/10.1364/OL.39.005788, 2014. a
Bouniol, D., Protat, A., Delanoë, J., Pelon, J., Piriou, J.-M., Bouyssel,
F., Tompkins, A. M., Wilson, D. R., Morille, Y., Haeffelin, M., O’Connor, E. J., Hogan, R. J., Illingworth, A. J., Donovan, D. P., and Baltink, H.: Using
continuous ground-based radar and lidar measurements for evaluating the
representation of clouds in four operational models, J. Appl.
Meteorol. Climatol., 49, 1971–1991, https://doi.org/10.1175/2010JAMC2333.1,
2010. a
Bréon, F.-M. and Doutriaux-Boucher, M.: A comparison of cloud droplet radii
measured from space, IEEE T. Geosci. Remote, 43,
1796–1805, https://doi.org/10.1109/TGRS.2005.852838, 2005. a, b
Bréon, F.-M. and Colzy, S.: Global distribution of cloud droplet effective
radius from POLDER polarization measurements, Geophys. Res. Lett.,
27, 4065–4068, https://doi.org/10.1029/2000GL011691, 2000. a
Campbell, J. R., Hlavka, D. L., Welton, E. J., Flynn, C. J., Turner, D. D.,
Spinhirne, J. D., Scott III, V. S., and Hwang, I.: Full-time, eye-safe cloud
and aerosol lidar observation at atmospheric radiation measurement program
sites: Instruments and data processing, J. Atmos. Ocean.
Tech., 19, 431–442,
https://doi.org/10.1175/1520-0426(2002)019<0431:FTESCA>2.0.CO;2, 2002. a, b
Cazorla, A., Casquero-Vera, J. A., Román, R., Guerrero-Rascado, J. L., Toledano, C., Cachorro, V. E., Orza, J. A. G., Cancillo, M. L., Serrano, A., Titos, G., Pandolfi, M., Alastuey, A., Hanrieder, N., and Alados-Arboledas, L.: Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula, Atmos. Chem. Phys., 17, 11861–11876, https://doi.org/10.5194/acp-17-11861-2017, 2017. a
Chan, K. L., Wiegner, M., Flentje, H., Mattis, I., Wagner, F., Gasteiger, J., and Geiß, A.: Evaluation of ECMWF-IFS (version 41R1) operational model forecasts of aerosol transport by using ceilometer network measurements, Geosci. Model Dev., 11, 3807–3831, https://doi.org/10.5194/gmd-11-3807-2018, 2018. a
Chang, F. and Li, Z.: The effect of droplet size distribution on the
determination of cloud droplet effective radius, in: 11th ARM Science Team
Meeting, Atlanta, Ga, 19–23, 2001. a
Chepfer, H., Chiriaco, M., Vautard, R., and Spinhirne, J.: Evaluation of MM5
optically thin clouds over Europe in fall using ICESat lidar spaceborne
observations, Mon. Weather Rev., 135, 2737–2753,
https://doi.org/10.1175/MWR3413.1, 2007. a, b, c
Chepfer, H., Bony, S., Winker, D., Chiriaco, M., Dufresne, J.-L., and Sèze,
G.: Use of CALIPSO lidar observations to evaluate the cloudiness simulated by
a climate model, Geophys. Res. Lett., 35, L15704,
https://doi.org/10.1029/2008GL034207, 2008. a, b, c, d
Chiriaco, M., Vautard, R., Chepfer, H., Haeffelin, M., Dudhia, J., Wanherdrick,
Y., Morille, Y., and Protat, A.: The ability of MM5 to simulate ice clouds:
Systematic comparison between simulated and measured fluxes and lidar/radar
profiles at the SIRTA atmospheric observatory, Mon. Weather Rev., 134,
897–918, https://doi.org/10.1175/MWR3102.1, 2006. a, b, c, d, e, f, g
Chiriaco, M., Dupont, J.-C., Bastin, S., Badosa, J., Lopez, J., Haeffelin, M., Chepfer, H., and Guzman, R.: ReOBS: a new approach to synthesize long-term multi-variable dataset and application to the SIRTA supersite, Earth Syst. Sci. Data, 10, 919–940, https://doi.org/10.5194/essd-10-919-2018, 2018. a, b
Costa-Surós, M., Calbó, J., González, J., and Martin-Vide, J.: Behavior of
cloud base height from ceilometer measurements, Atmos. Res., 127,
64–76, https://doi.org/10.1016/j.atmosres.2013.02.005, 2013. a
Cromwell, E. and Flynn, D.: Lidar Cloud Detection With Fully Convolutional Networks, 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa Village, HI, USA, 619–627, https://doi.org/10.1109/WACV.2019.00071, 2019. a
Cromwell, E. and Flynn, D.: Lidar cloud detection with fully convolutional
networks, in: 2019 IEEE Winter Conference on Applications of Computer Vision
(WACV), 619–627, IEEE, 2019. a
Dee, D. P., Uppala, S. M., Simmons, A., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M., Balsamo, G., Bauer, d. P., et al.: The
ERA-Interim reanalysis: Configuration and performance of the data
assimilation system, Q. J. Roy. Meteorol. Soc.,
137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Diner, D. J., Beckert, J. C., Reilly, T. H., Bruegge, C. J., Conel, J. E.,
Kahn, R. A., Martonchik, J. V., Ackerman, T. P., Davies, R., Gerstl, S. A. W., Gordon, H. R., Muller, J.. Myneni, R. B., Sellers, P. J., Pinty, B., and Verstraete, M. M.: Multi-angle Imaging SpectroRadiometer (MISR) instrument description
and experiment overview, IEEE T. Geosci. Remote,
36, 1072–1087, https://doi.org/10.1109/36.700992, 1998. a
Dionisi, D., Barnaba, F., Diémoz, H., Di Liberto, L., and Gobbi, G. P.: A multiwavelength numerical model in support of quantitative retrievals of aerosol properties from automated lidar ceilometers and test applications for AOT and PM10 estimation, Atmos. Meas. Tech., 11, 6013–6042, https://doi.org/10.5194/amt-11-6013-2018, 2018. a
Ebita, A., Kobayashi, S., Ota, Y., Moriya, M., Kumabe, R., Onogi, K., Harada,
Y., Yasui, S., Miyaoka, K., Takahashi, K., Kamahori, H., Kobayashi, C., Endo, H., Soma, M., Oikawa, Y., and Ishimizu, T.: The Japanese 55-year
reanalysis “JRA-55”: an interim report, Sola, 7, 149–152,
https://doi.org/10.2151/jmsj.2016-015, 2011. a
ECMWF: Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation
of ECMWF atmospheric reanalyses of the global climate, Copernicus Climate
Change Service Climate Data Store (CDS), https://doi.org/10.24381/cds.bd0915c6, available at:
https://cds.climate.copernicus.eu/cdsapp#!/home (last access: 1 January 2021), 2019. a
Edwards, J. and Slingo, A.: Studies with a flexible new radiation code. I:
Choosing a configuration for a large-scale model, Q. J.
Roy. Meteorol. Soc., 122, 689–719, https://doi.org/10.1002/qj.49712253107,
1996. a
Emeis, S.: Surface-based remote sensing of the atmospheric boundary layer,
vol. 40, Springer Science & Business Media, https://doi.org/10.1007/978-90-481-9340-0,
2010. a, b, c
Emeis, S., Schäfer, K., and Münkel, C.: Observation of the structure of
the urban boundary layer with different ceilometers and validation by RASS
data, Meteorol. Z., 18, 149–154,
https://doi.org/10.1127/0941-2948/2009/0365, 2009. a
Eresmaa, N., Karppinen, A., Joffre, S. M., Räsänen, J., and Talvitie, H.: Mixing height determination by ceilometer, Atmos. Chem. Phys., 6, 1485–1493, https://doi.org/10.5194/acp-6-1485-2006, 2006. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Eyring, V., Cox, P. M., Flato, G. M., Gleckler, P. J., Abramowitz, G.,
Caldwell, P., Collins, W. D., Gier, B. K., Hall, A. D., Hoffman, F. M.,
Hurtt, G. C., Jahn, A., Jones, C. D., Klein, S. A., Krasting, J. P., Kwiatkowski, L., Lorenz, R., Maloney, E., Meehl, G. A., Pendergrass, A. G., Pincus, R., Ruane, A. C., Russell, J. L., Sanderson, B. M., Santer, B. D., Sherwood, S. C., Simpson, I. R., Stouffer, R. J., and Williamson, M. S.: Taking climate model evaluation to the next level, Nat. Clim.
Change, 9, 102–110, https://doi.org/10.1038/s41558-018-0355-y, 2019. a
Flynn, C. J., Mendozaa, A., Zhengb, Y., and Mathurb, S.: Novel
polarization-sensitive micropulse lidar measurement technique, Opt.
Exp., 15, 2785–2790, https://doi.org/10.1364/OE.15.002785, 2007. a
Fu, D., Di Girolamo, L., Liang, L., and Zhao, G.: Regional Biases in MODIS
Marine Liquid Water Cloud Drop Effective Radius Deduced Through Fusion With
MISR, J. Geophys. Res.-Atmos., 124, 13182–13196,
https://doi.org/10.1029/2019JD031063, 2019. a
Garnier, A., Pelon, J., Vaughan, M. A., Winker, D. M., Trepte, C. R., and Dubuisson, P.: Lidar multiple scattering factors inferred from CALIPSO lidar and IIR retrievals of semi-transparent cirrus cloud optical depths over oceans, Atmos. Meas. Tech., 8, 2759–2774, https://doi.org/10.5194/amt-8-2759-2015, 2015. a, b, c, d, e, f, g
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L.,
Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The
modern-era retrospective analysis for research and applications, version 2
(MERRA-2), J. Climate, 30, 5419–5454,
https://doi.org/10.1175/JCLI-D-16-0758.1, 2017. a
Geleyn, J. and Hollingsworth, A.: An economical analytical method for the
computation of the interaction between scattering and line absorption of
radiation, Contributions to Atmospheric Physics, 52, 1–16, 1979. a
Goody, R. M. and Yung, Y. L.: Atmospheric radiation: theoretical basis, Oxford
University Press, New York, NY, USA, 2 edn., 1995. a
Hansen, A., Ament, F., Grützun, V., and Lammert, A.: Model evaluation by a cloud classification based on multi-sensor observations, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-259, 2018a. a
Hansen, A., Ament, F., Grützun, V., and Lammert, A.: Model evaluation by a cloud classification based on multi-sensor observations, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-259, 2018b. a
Harada, Y., Kamahori, H., Kobayashi, C., Endo, H., Kobayashi, S., Ota, Y.,
Onoda, H., Onogi, K., Miyaoka, K., and Takahashi, K.: The JRA-55 Reanalysis:
Representation of atmospheric circulation and climate variability, J. Meteorol. Soc. Japan. Ser. II, 94, 269–302,
https://doi.org/10.2151/jmsj.2016-015, 2016. a
Heese, B., Flentje, H., Althausen, D., Ansmann, A., and Frey, S.: Ceilometer lidar comparison: backscatter coefficient retrieval and signal-to-noise ratio determination, Atmos. Meas. Tech., 3, 1763–1770, https://doi.org/10.5194/amt-3-1763-2010, 2010. a
Heymsfield, A. J.: Extinction-ice water content-effective radius algorithms for
CALIPSO, Geophys. Res. Lett., 32, L10807, https://doi.org/10.1029/2005gl022742,
2005. a, b, c, d
Hines, K. M. and Bromwich, D. H.: Development and testing of Polar Weather
Research and Forecasting (WRF) model. Part I: Greenland ice sheet
meteorology, Mon. Weather Rev., 136, 1971–1989,
https://doi.org/10.1175/2007MWR2112.1, 2008. a
Hogan, R. J.: Fast approximate calculation of multiply scattered lidar returns,
Appl. Opt., 45, 5984–5992, https://doi.org/10.1364/AO.45.005984, 2006. a, b, c
Hogan, R. J., Jakob, C., and Illingworth, A. J.: Comparison of ECMWF
Winter-Season Cloud Fraction with Radar-Derived Values, J. Appl.
Meteorol., 40, 513–525,
https://doi.org/10.1175/1520-0450(2001)040<0513:COEWSC>2.0.CO;2, 2001. a
Hopkin, E.: Use of a calibrated ceilometer network to improve high resolution
weather forecasts, Ph.D. thesis, University of Reading, UK, 2018. a
Hopkin, E., Illingworth, A. J., Charlton-Perez, C., Westbrook, C. D., and Ballard, S.: A robust automated technique for operational calibration of ceilometers using the integrated backscatter from totally attenuating liquid clouds, Atmos. Meas. Tech., 12, 4131–4147, https://doi.org/10.5194/amt-12-4131-2019, 2019. a, b, c, d, e, f, g, h, i, j, k, l
Hourdin, F., Mauritsen, T., Gettelman, A., Golaz, J.-C., Balaji, V., Duan, Q.,
Folini, D., Ji, D., Klocke, D., Qian, Y., Rauser, F., Rio, C., Tomassini, L., Watanabe, M., and Williamson, D. : The art and science of
climate model tuning, B. Am. Meteorol. Soc., 98,
589–602, https://doi.org/10.1175/BAMS-D-15-00135.1, 2017. a
Hu, Y.: Depolarization ratio–effective lidar ratio relation: Theoretical
basis for space lidar cloud phase discrimination, Geophys. Res.
Lett., 34, L11812, https://doi.org/10.1029/2007GL029584, 2007. a
Hu, Y., Vaughan, M., McClain, C., Behrenfeld, M., Maring, H., Anderson, D., Sun-Mack, S., Flittner, D., Huang, J., Wielicki, B., Minnis, P., Weimer, C., Trepte, C., and Kuehn, R.: Global statistics of liquid water content and effective number concentration of water clouds over ocean derived from combined CALIPSO and MODIS measurements, Atmos. Chem. Phys., 7, 3353–3359, https://doi.org/10.5194/acp-7-3353-2007, 2007. a
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci.
Eng., 9, 90, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Illingworth, A., Hogan, R., O'connor, E., Bouniol, D., Brooks, M., Delanoë,
J., Donovan, D., Eastment, J., Gaussiat, N., Goddard, J. W. F., Haeffelin, M., Baltink, H. K., Krasnov, O. A., Pelon, J., Piriou, J.-M., Protat, A., Russchenberg, H. W. J., Seifert, A., Tompkins, A. M., van Zadelhoff, G.-J., Vinit, F., Willén, U., Wilson, D. R., and Wrench, C. L.: Cloudnet:
Continuous evaluation of cloud profiles in seven operational models using
ground-based observations, B. Am. Meteorol. Soc.,
88, 883–898, https://doi.org/10.1175/BAMS-88-6-883, 2007. a, b
Illingworth, A., Cimini, D., Haefele, A., Haeffelin, M., Hervo, M., Kotthaus,
S., Löhnert, U., Martinet, P., Mattis, I., O’Connor, E. J., and Potthast, R.: How
can Existing Ground-Based Profiling Instruments Improve European Weather
Forecasts?, B. Am. Meteorol. Soc., 100, 605–619,
https://doi.org/10.1175/BAMS-D-17-0231.1, 2018. a, b
Illingworth, A. J., Barker, H., Beljaars, A., Ceccaldi, M., Chepfer, H.,
Clerbaux, N., Cole, J., Delanoë, J., Domenech, C., Donovan, D. P.,
Fukuda, S., Hirakata, M., Hogan, R. J., Huenerbein, A., Kollias, P., Kubota, T., Nakajima, T., Nakajima, T. Y., Nishizawa, T., Ohno, Y., Okamoto, H., Oki, R., Sato, K., Satoh, M., Shephard, M. W., Velázquez-Blázquez, A., Wandinger, U., Wehr, T., and van Zadelhoff, G.-J.: The EarthCARE satellite: The next step forward in global measurements
of clouds, aerosols, precipitation, and radiation, B. Am.
Meteorol. Soc., 96, 1311–1332, https://doi.org/10.1175/BAMS-D-12-00227.1,
2015a. a
Illingworth, A. J., Cimini, D., Gaffard, C., Haeffelin, M., Lehmann, V.,
Löhnert, U., O’Connor, E. J., and Ruffieux, D.: Exploiting existing
ground-based remote sensing networks to improve high-resolution weather
forecasts, B. Am. Meteorol. Soc., 96, 2107–2125,
https://doi.org/10.1175/BAMS-D-13-00283.1, 2015b. a
Jin, Y., Kai, K., Kawai, K., Nagai, T., Sakai, T., Yamazaki, A., Uchiyama, A.,
Batdorj, D., Sugimoto, N., and Nishizawa, T.: Ceilometer calibration for
retrieval of aerosol optical properties, J. Quant. Spectrosc. Ra., 153, 49–56, https://doi.org/10.1016/j.jqsrt.2014.10.009, 2015. a, b, c
Josset, D., Pelon, J., Garnier, A., Hu, Y., Vaughan, M., Zhai, P.-W., Kuehn,
R., and Lucker, P.: Cirrus optical depth and lidar ratio retrieval from
combined CALIPSO-CloudSat observations using ocean surface echo, J. Geophys. Res.-Atmos., 117, D05207,
https://doi.org/10.1029/2011jd016959, 2012. a
Klein, S. A. and Jakob, C.: Validation and sensitivities of frontal clouds
simulated by the ECMWF model, Mon. Weather Rev., 127, 2514–2531,
https://doi.org/10.1175/1520-0493(1999)127<2514:VASOFC>2.0.CO;2, 1999. a
Klekociuk, A. R., French, W. J. R., Alexander, S. P., Kuma, P., and McDonald,
A. J.: The state of the atmosphere in the 2016 southern Kerguelen Axis
campaign region, Deep Sea Res. Pt. II, 174, 0967-0645,
https://doi.org/10.1016/j.dsr2.2019.02.001, 2019. a
Knepp, T. N., Szykman, J. J., Long, R., Duvall, R. M., Krug, J., Beaver, M., Cavender, K., Kronmiller, K., Wheeler, M., Delgado, R., Hoff, R., Berkoff, T., Olson, E., Clark, R., Wolfe, D., Van Gilst, D., and Neil, D.: Assessment of mixed-layer height estimation from single-wavelength ceilometer profiles, Atmos. Meas. Tech., 10, 3963–3983, https://doi.org/10.5194/amt-10-3963-2017, 2017. a
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi,
K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Takahashi, K.: The JRA-55 reanalysis:
General specifications and basic characteristics, J.
Meteorol. Soc. Japan. Ser. II, 93, 5–48,
https://doi.org/10.2151/jmsj.2015-001, 2015. a
Kotthaus, S., O'Connor, E., Münkel, C., Charlton-Perez, C., Haeffelin, M., Gabey, A. M., and Grimmond, C. S. B.: Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers, Atmos. Meas. Tech., 9, 3769–3791, https://doi.org/10.5194/amt-9-3769-2016, 2016. a, b, c, d
Kuma, P.: cl2nc 3.3.0, Zenodo, https://doi.org/10.5281/zenodo.4409716, 2020a. a
Kuma, P.: mpl2nc 1.3.5, Zenodo, https://doi.org/10.5281/zenodo.4409731, 2020b. a
Kuma, P., McDonald, A. J., Morgenstern, O., Alexander, S. P., Cassano, J. J., Garrett, S., Halla, J., Hartery, S., Harvey, M. J., Parsons, S., Plank, G., Varma, V., and Williams, J.: Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations, Atmos. Chem. Phys., 20, 6607–6630, https://doi.org/10.5194/acp-20-6607-2020, 2020. a, b, c
Kuma, P., McDonald, A. J., Morgenstern, O., Querel, R., Silber, I., and Flynn, C. J.: Automatic Lidar and Ceilometer Framework (ALCF) (Version 1.0.0), Zenodo, https://doi.org/10.5281/zenodo.4411633, 2021. 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
Lewis, J. R., Campbell, J. R., Welton, E. J., Stewart, S. A., and Haftings,
P. C.: Overview of MPLNET version 3 cloud detection, J. Atmos. Ocean. Tech., 33, 2113–2134, https://doi.org/10.1175/JTECH-D-15-0190.1,
2016. a
Liou, K.-N.: An introduction to atmospheric radiation, vol. 84, Elsevier, 2
edn., 2002. a
Liu, J., Li, Z., Zheng, Y., and Cribb, M.: Cloud-base distribution and cirrus
properties based on micropulse lidar measurements at a site in southeastern
China, Adv. Atmos. Sci., 32, 991–1004,
https://doi.org/10.1007/s00376-014-4176-2, 2015a. a
Liu, L., Sun, X.-J., Liu, X.-C., Gao, T.-C., and Zhao, S.-J.: Comparison of
cloud base height derived from a ground-based infrared cloud measurement and
two ceilometers, Adv. Meteorol., 2015, 1687-9309, https://doi.org/10.1155/2015/853861,
2015b. a, b
Madonna, F., Rosoldi, M., Lolli, S., Amato, F., Vande Hey, J., Dhillon, R., Zheng, Y., Brettle, M., and Pappalardo, G.: Intercomparison of aerosol measurements performed with multi-wavelength Raman lidars, automatic lidars and ceilometers in the framework of INTERACT-II campaign, Atmos. Meas. Tech., 11, 2459–2475, https://doi.org/10.5194/amt-11-2459-2018, 2018. a, b
Marenco, F., Santacesaria, V., Bais, A. F., Balis, D., di Sarra, A.,
Papayannis, A., and Zerefos, C.: Optical properties of tropospheric aerosols
determined by lidar and spectrophotometric measurement (Photochemical
Activity and Solar Ultraviolet Radiation campaign), Appl. Opt., 36,
6875–6886, https://doi.org/10.1364/AO.36.006875, 1997. a
Martucci, G., Milroy, C., and O’Dowd, C. D.: Detection of cloud-base height
using Jenoptik CHM15K and Vaisala CL31 ceilometers, J. Atmos. Ocean. Tech., 27, 305–318, https://doi.org/10.1175/2009JTECHA1326.1, 2010. a, b
Masunaga, H., Matsui, T., Tao, W.-k., Hou, A. Y., Kummerow, C. D., Nakajima,
T., Bauer, P., Olson, W. S., Sekiguchi, M., and Nakajima, T. Y.: Satellite
data simulator unit: A multisensor, multispectral satellite simulator
package, B. Am. Meteorol. Soc., 91, 1625–1632,
https://doi.org/10.1175/2010BAMS2809.1, 2010. a
Matsui, T.: Goddard Satellite Data Simulator Unit (G-SDSU), https://cloud.gsfc.nasa.gov/index.php?section=14 (last access: January 2021),
2019. a
Mattis, I., Begbie, R., Boyouk, N., Bravo-Aranda, J. A., Brettle, M.,
Cermak, J., Drouin, M.-A., Geiß, A., Görsdorf, U., Haefele,
A., Haeffelin, M., Hervo, M., Komínková, K., Leinweber, R.,
Müller, G., Münkel, C., Pattantyús-Ábrahám, M.,
Pönitz, K., Wagner, F., and Wiegner, M.: The ceilometer
inter-comparison campaign CeiLinEx2015, in: EGU General Assembly Conference
Abstracts, EPSC2016–9687, 2016. a, b
McGill, M. J., Yorks, J. E., Scott, V. S., Kupchock, A. W., and Selmer, P. A.:
The Cloud-Aerosol Transport System (CATS): A technology demonstration on the
International Space Station, in: Lidar Remote Sensing for Environmental
Monitoring XV, vol. 9612, p. 96120A, International Society for Optics and
Photonics, 2015. a
Mie, G.: Beiträge zur Optik trüber Medien, speziell kolloidaler
Metallösungen, Annalen der Physik, 330, 377–445,
https://doi.org/10.1002/andp.19083300302, 1908. a
Milroy, C., Martucci, G., Lolli, S., Loaec, S., Sauvage, L., Xueref-Remy, I.,
Lavrič, J. V., Ciais, P., Feist, D. G., Biavati, G., and O'Dowd, C. D.: An
assessment of pseudo-operational ground-based light detection and ranging
sensors to determine the boundary-layer structure in the coastal atmosphere,
Adv. Meteorol., 2012, 929080, https://doi.org/10.1155/2012/929080, 2012. a
Morcrette, C. J., O'Connor, E. J., and Petch, J. C.: Evaluation of two cloud
parametrization schemes using ARM and Cloud-Net observations, Q.
J. Roy. Meteorol. Soc., 138, 964–979,
https://doi.org/10.1002/qj.969, 2012. a
Morille, Y., Haeffelin, M., Drobinski, P., and Pelon, J.: STRAT: An automated
algorithm to retrieve the vertical structure of the atmosphere from
single-channel lidar data, J. Atmos. Ocean. Tech.,
24, 761–775, https://doi.org/10.1175/JTECH2008.1, 2007. a, b
Münkel, C., Eresmaa, N., Räsänen, J., and Karppinen, A.: Retrieval
of mixing height and dust concentration with lidar ceilometer, Bound.-Lay.
Meteorol., 124, 117–128, https://doi.org/10.1007/s10546-006-9103-3, 2007. a
NASA JPL: NASA Shuttle Radar Topography Mission Global 3 arc second [Data
set], NASA EOSDIS Land Processes DAAC,
https://doi.org/10.5067/MEaSUREs/SRTM/SRTMGL3.003, 2013. a
Noel, V. and Chepfer, H.: A global view of horizontally oriented crystals in
ice clouds from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite
Observation (CALIPSO), J. Geophys. Res., 115, D00H23,
https://doi.org/10.1029/2009jd012365, 2010. a
O'Connor, E. J., Illingworth, A. J., and Hogan, R. J.: A technique for
autocalibration of cloud lidar, J. Atmos. Ocean.
Tech., 21, 777–786,
https://doi.org/10.1175/1520-0426(2004)021<0777:ATFAOC>2.0.CO;2, 2004. a, b, c
Pal, S. R., Steinbrecht, W., and Carswell, A. I.: Automated method for lidar
determination of cloud-base height and vertical extent, Appl. Opt., 31,
1488–1494, https://doi.org/10.1364/AO.31.001488, 1992. a
Parkinson, C. L.: Aqua: An Earth-observing satellite mission to examine water
and other climate variables, IEEE T. Geosci. Remote, 41, 173–183, https://doi.org/10.1109/TGRS.2002.808319, 2003. a
Petty, G. W. and Huang, W.: The modified gamma size distribution applied to
inhomogeneous and nonspherical particles: Key relationships and conversions,
J. Atmos. Sci., 68, 1460–1473,
https://doi.org/10.1175/2011JAS3645.1, 2011. a, b, c
Powers, J. G., Monaghan, A. J., Cayette, A. M., Bromwich, D. H., Kuo, Y.-H.,
and Manning, K. W.: Real-Time Mesoscale Modeling Over Antarctica: The
Antarctic Mesoscale Prediction System, B. Am.
Meteorol. Soc., 84, 1533–1546, https://doi.org/10.1175/BAMS-84-11-1533, 2003. a
Price-Whelan, A. M., Sipőcz, B. M., Günther, H. M., et al.: The
Astropy Project: Building an Open-science Project and Status of the v2.0 Core
Package, Astronomical J., 156, 123, https://doi.org/10.3847/1538-3881/aabc4f,
2018. a
R Core Team: R: A Language and Environment for Statistical Computing, R
Foundation for Statistical Computing, Vienna, Austria, available at:
https://www.R-project.org/ (last access: 1 January 2021), 2017. a
Rausch, J., Meyer, K., Bennartz, R., and Platnick, S.: Differences in liquid cloud droplet effective radius and number concentration estimates between MODIS collections 5.1 and 6 over global oceans, Atmos. Meas. Tech., 10, 2105–2116, https://doi.org/10.5194/amt-10-2105-2017, 2017. a
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V.,
Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface
temperature, sea ice, and night marine air temperature since the late
nineteenth century, J. Geophys. Res.-Atmos., 108, 4407,
https://doi.org/10.1029/2002JD002670, 2003. a
Rew, R. and Davis, G.: NetCDF: an interface for scientific data access, IEEE
Comput. Graph. Appl., 10, 76–82, https://doi.org/10.1109/38.56302, 1990. a
Rosoldi, M., Madonna, F., Pappalardo, G., Hey, J. V., and Zheng, Y.: The lesson
learnt during interact-I and INTERACT-II actris measurement campaigns, in:
EPJ Web of Conferences, vol. 176, p. 11002, EDP Sciences, 2018. a
Rossow, W. B. and Schiffer, R. A.: ISCCP cloud data products, B.
Am. Meteorol. Soc., 72, 2–20,
https://doi.org/10.1175/1520-0477(1991)072<0002:ICDP>2.0.CO;2, 1991. a
Rossum, G.: Python reference manual, Centre for Mathematics and Computer Science, Amsterdam, Netherlands, 1995. a
Schmidt, G. A., Bader, D., Donner, L. J., Elsaesser, G. S., Golaz, J.-C., Hannay, C., Molod, A., Neale, R. B., and Saha, S.: Practice and philosophy of climate model tuning across six US modeling centers, Geosci. Model Dev., 10, 3207–3223, https://doi.org/10.5194/gmd-10-3207-2017, 2017. a
Silber, I., Verlinde, J., Eloranta, E. W., Flynn, C. J., and Flynn, D. M.:
Polar liquid cloud base detection algorithms for high spectral resolution or
micropulse lidar data, J. Geophys. Res.-Atmos., 123,
4310–4322, https://doi.org/10.1029/2017JD027840, 2018. a, b, c, d
Spinhirne, J. D.: Micro pulse lidar, IEEE T. Geosci. Remote, 31, 48–55, 1993. a
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z.,
Illingworth, A. J., O'Connor, E. J., Rossow, W. B., Durden, S. L., Miller, S. D., Austin, R. T., Benedetti, A., Mitrescu, C., and the CloudSat Science Team:
The CloudSat mission and the A-Train: A new dimension of space-based
observations of clouds and precipitation, B. Am.
Meteorol. Soc., 83, 1771–1790, https://doi.org/10.1175/BAMS-83-12-1771, 2002. a
Stokes, G. M. and Schwartz, S. E.: The Atmospheric Radiation Measurement (ARM)
Program: Programmatic background and design of the cloud and radiation test
bed, B. Am. Meteorol. Soc., 75, 1201–1222,
https://doi.org/10.1175/1520-0477(1994)075<1201:TARMPP>2.0.CO;2, 1994. a
Swales, D. J., Pincus, R., and Bodas-Salcedo, A.: The Cloud Feedback Model Intercomparison Project Observational Simulator Package: Version 2, Geosci. Model Dev., 11, 77–81, https://doi.org/10.5194/gmd-11-77-2018, 2018. a
Telford, P. J., Braesicke, P., Morgenstern, O., and Pyle, J. A.: Technical Note: Description and assessment of a nudged version of the new dynamics Unified Model, Atmos. Chem. Phys., 8, 1701–1712, https://doi.org/10.5194/acp-8-1701-2008, 2008. a
Torvalds, L.: Linux: a portable operating system, Master's thesis, University
of Helsinki, 1997. a
Tsaknakis, G., Papayannis, A., Kokkalis, P., Amiridis, V., Kambezidis, H. D., Mamouri, R. E., Georgoussis, G., and Avdikos, G.: Inter-comparison of lidar and ceilometer retrievals for aerosol and Planetary Boundary Layer profiling over Athens, Greece, Atmos. Meas. Tech., 4, 1261–1273, https://doi.org/10.5194/amt-4-1261-2011, 2011. a
Van Der Walt, S., Colbert, S. C., and Varoquaux, G.: The NumPy array: a
structure for efficient numerical computation, Comput. Sci.
Eng., 13, 22–30, https://doi.org/10.1109/MCSE.2011.37, 2011. a
van Diedenhoven, B.: Remote Sensing of Crystal Shapes in Ice Clouds, in:
Springer Series in Light Scattering, pp. 197–250, Springer International
Publishing, https://doi.org/10.1007/978-3-319-70808-9_5, 2017. a
Van Tricht, K., Gorodetskaya, I. V., Lhermitte, S., Turner, D. D., Schween, J. H., and Van Lipzig, N. P. M.: An improved algorithm for polar cloud-base detection by ceilometer over the ice sheets, Atmos. Meas. Tech., 7, 1153–1167, https://doi.org/10.5194/amt-7-1153-2014, 2014. a, b
Vaughan, M. A., Liu, Z., McGill, M. J., Hu, Y., and Obland, M. D.: On the
spectral dependence of backscatter from cirrus clouds: Assessing CALIOP's
1064 nm calibration assumptions using cloud physics lidar measurements,
J. Geophys. Res.-Atmos., 115, D14206,
https://doi.org/10.1029/2009JD013086, 2010. a
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T.,
Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright,
J., van der Walt, S. J., Brett, M., Wilson, J., Jarrod Millman, K.,
Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E.,
Carey, C., Polat, İ., Feng, Y., Moore, E. W., Vand erPlas, J.,
Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero,
E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa,
F., van Mulbregt, P., and Contributors: SciPy 1.0–Fundamental
Algorithms for Scientific Computing in Python, arXiv [preprint], arXiv:1907.10121, 11 December 2019. a
Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Carslaw, K., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Jones, C., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and Zerroukat, M.: The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations, Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, 2019. a
Wang, Z. and Sassen, K.: Cloud type and macrophysical property retrieval using
multiple remote sensors, J. Appl. Meteorol., 40, 1665–1682,
https://doi.org/10.1175/1520-0450(2001)040<1665:CTAMPR>2.0.CO;2, 2001. a, b
Warren, E., Charlton-Perez, C., Kotthaus, S., Lean, H., Ballard, S., Hopkin,
E., and Grimmond, S.: Evaluation of forward-modelled attenuated backscatter
using an urban ceilometer network in London under clear-sky conditions,
Atmos. Environ., 191, 532–547,
https://doi.org/10.1016/j.atmosenv.2018.04.045, 2018. a
Watson-Parris, D., Schutgens, N., Cook, N., Kipling, Z., Kershaw, P., Gryspeerdt, E., Lawrence, B., and Stier, P.: Community Intercomparison Suite (CIS) v1.4.0: a tool for intercomparing models and observations, Geosci. Model Dev., 9, 3093–3110, https://doi.org/10.5194/gmd-9-3093-2016, 2016. a
Webb, M., Senior, C., Bony, S., and Morcrette, J.-J.: Combining ERBE and ISCCP
data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate
models, Clim. Dynam., 17, 905–922, https://doi.org/10.1007/s003820100157, 2001. a
Webb, M. J., Andrews, T., Bodas-Salcedo, A., Bony, S., Bretherton, C. S., Chadwick, R., Chepfer, H., Douville, H., Good, P., Kay, J. E., Klein, S. A., Marchand, R., Medeiros, B., Siebesma, A. P., Skinner, C. B., Stevens, B., Tselioudis, G., Tsushima, Y., and Watanabe, M.: The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6, Geosci. Model Dev., 10, 359–384, https://doi.org/10.5194/gmd-10-359-2017, 2017. a
Welton, E. J., Voss, K. J., Gordon, H. R., Maring, H., Smirnov, A., Holben, B.,
Schmid, B., Livingston, J. M., Russell, P. B., Durkee, P. A., Formenti, P., and Andreae, M. O.:
Ground-based lidar measurements of aerosols during ACE-2: Instrument
description, results, and comparisons with other ground-based and airborne
measurements, Tellus B, 52, 636–651, https://doi.org/10.1034/j.1600-0889.2000.00025.x,
2000. a
Welton, E. J., Voss, K. J., Quinn, P. K., Flatau, P. J., Markowicz, K.,
Campbell, J. R., Spinhirne, J. D., Gordon, H. R., and Johnson, J. E.:
Measurements of aerosol vertical profiles and optical properties during
INDOEX 1999 using micropulse lidars, J. Geophys. Res.-Atmos., 107, INX2–18, https://doi.org/10.1029/2000JD000038, 2002. a
Welton, E. J., Campbell, J. R., Berkoff, T. A., Valencia, S., Spinhirne, J. D.,
Holben, B., Tsay, S.-C., and Schmid, B.: The NASA Micro-Pulse Lidar Network
(MPLNET): an overview and recent results, Opt. Pur. Apl, 39, 67–74, 2006. a
Werner, M.: Shuttle radar topography mission (SRTM) mission overview,
Frequenz, 55, 75–79, https://doi.org/10.1515/FREQ.2001.55.3-4.75, 2001. a
Wiegner, M. and Gasteiger, J.: Correction of water vapor absorption for aerosol remote sensing with ceilometers, Atmos. Meas. Tech., 8, 3971–3984, https://doi.org/10.5194/amt-8-3971-2015, 2015. a, b, c, d
Wiegner, M. and Geiß, A.: Aerosol profiling with the Jenoptik ceilometer CHM15kx, Atmos. Meas. Tech., 5, 1953–1964, https://doi.org/10.5194/amt-5-1953-2012, 2012. a
Wiegner, M., Madonna, F., Binietoglou, I., Forkel, R., Gasteiger, J., Geiß, A., Pappalardo, G., Schäfer, K., and Thomas, W.: What is the benefit of ceilometers for aerosol remote sensing? An answer from EARLINET, Atmos. Meas. Tech., 7, 1979–1997, https://doi.org/10.5194/amt-7-1979-2014, 2014. a, b, c, d
Wiegner, M., Mattis, I., Pattantyús-Ábrahám, M., Bravo-Aranda, J. A., Poltera, Y., Haefele, A., Hervo, M., Görsdorf, U., Leinweber, R., Gasteiger, J., Haeffelin, M., Wagner, F., Cermak, J., Komínková, K., Brettle, M., Münkel, C., and Pönitz, K.: Aerosol backscatter profiles from ceilometers: validation of water vapor correction in the framework of CeiLinEx2015, Atmos. Meas. Tech., 12, 471–490, https://doi.org/10.5194/amt-12-471-2019, 2019. a, b
Williams, D. N., Ananthakrishnan, R., Bernholdt, D., Bharathi, S., Brown, D.,
Chen, M., Chervenak, A., Cinquini, L., Drach, R., Foster, I., et al.: The
Earth System Grid: Enabling access to multimodel climate simulation data,
B. Am. Meteorol. Soc., 90, 195–206,
https://doi.org/10.1175/2008BAMS2459.1, 2009. a
Williams, J., Morgenstern, O., Varma, V., Behrens, E., Hayek, W., Oliver, H.,
Dean, S., Mullan, B., and Frame, D.: Development of the New Zealand Earth
System Model: NZESM, Weather and Climate, 36, 25–44, https://doi.org/10.2307/26779386,
2016. a
Williams, K. D. and Bodas-Salcedo, A.: A multi-diagnostic approach to cloud evaluation, Geosci. Model Dev., 10, 2547–2566, https://doi.org/10.5194/gmd-10-2547-2017, 2017. a
Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., Hunt,
W. H., and Young, S. A.: Overview of the CALIPSO mission and CALIOP data
processing algorithms, J. Atmos. Ocean. Tech., 26,
2310–2323, https://doi.org/10.1175/2009JTECHA1281.1, 2009. a
Wiscombe, W. J.: Mie scattering calculations: Advances in technique and fast,
vector-speed computer codes, Tech. rep., National Center for Atmospheric
Research Boulder, Colorado, 1979. a
Wiscombe, W. J.: Improved Mie scattering algorithms, Appl. Opt., 19,
1505–1509, 1980. a
Yang, P., Liou, K.-N., Bi, L., Liu, C., Yi, B., and Baum, B. A.: On the
radiative properties of ice clouds: Light scattering, remote sensing, and
radiation parameterization, Adv. Atmos. Sci., 32, 32–63,
https://doi.org/10.1007/s00376-014-0011-z, 2014. a
Yorks, J. E., Hlavka, D. L., Hart, W. D., and McGill, M. J.: Statistics of
Cloud Optical Properties from Airborne Lidar Measurements, J.
Atmos. Ocean. Tech., 28, 869–883,
https://doi.org/10.1175/2011jtecha1507.1, 2011.
a
Zadra, A., Williams, K., Frassoni, A., Rixen, M., Adames, Á. F., Berner,
J., Bouyssel, F., Casati, B., Christensen, H., Ek, M. B., Flato, G., Huang, Y., Judt, F., Lin, H., Maloney, E., Merryfield, W., Van Niekerk, A., Rackow, T., Saito, K., Wedi, N., and Yadav, P.: Systematic
Errors in Weather and Climate Models: Nature, Origins, and Ways Forward,
B. Am. Meteorol. Soc., 99, ES67–ES70,
https://doi.org/10.1175/BAMS-D-17-0287.1, 2018. a
Zdunkowski, W., Trautmann, T., and Bott, A.: Radiation in the atmosphere: a
course in theoretical meteorology, Cambridge University Press, New York, NY, USA, 482 pp., ISBN 0-511-27560-9, 2007. a
Zhang, Y., Xie, S., Klein, S. A., Marchand, R., Kollias, P., Clothiaux, E. E.,
Lin, W., Johnson, K., Swales, D., Bodas-Salcedo, A., Tang, S., Haynes, J. M., Collis, S., Jensen, M., Bharadwaj, N., Hardin, J., and Isom, B.: The ARM Cloud
Radar Simulator for Global Climate Models: Bridging Field Data and Climate
Models, B. Am. Meteorol. Soc., 99, 21–26,
https://doi.org/10.1175/BAMS-D-16-0258.1, 2018. a
Zhang, Z. and Platnick, S.: An assessment of differences between cloud
effective particle radius retrievals for marine water clouds from three MODIS
spectral bands, J. Geophys. Res.-Atmos., 116, D20215,
https://doi.org/10.1029/2011JD016216, 2011. a
