Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4617-2021
© 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-14-4617-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model intercomparison of COSMO 5.0 and IFS 45r1 at kilometer-scale grid spacing
Christian Zeman
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Nils P. Wedi
European Centre for Medium-Range Weather Forecasts, Reading, UK
Peter D. Dueben
European Centre for Medium-Range Weather Forecasts, Reading, UK
Nikolina Ban
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Christoph Schär
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
EGUsphere, https://doi.org/10.5194/egusphere-2023-2263, https://doi.org/10.5194/egusphere-2023-2263, 2023
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We investigate the effects of reduced precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced precision implementations of their model.
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Weather Clim. Dynam., 4, 189–211, https://doi.org/10.5194/wcd-4-189-2023, https://doi.org/10.5194/wcd-4-189-2023, 2023
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We developed a vortex identification algorithm for realistic atmospheric simulations. The algorithm enabled us to obtain a climatology of vortex shedding from Madeira Island for a 10-year simulation period. This first objective climatological analysis of vortex streets shows consistency with observed atmospheric conditions. The analysis shows a pronounced annual cycle with an increasing vortex shedding rate from April to August and a sudden decrease in September.
Christian Zeman and Christoph Schär
Geosci. Model Dev., 15, 3183–3203, https://doi.org/10.5194/gmd-15-3183-2022, https://doi.org/10.5194/gmd-15-3183-2022, 2022
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Our atmosphere is a chaotic system, where even a tiny change can have a big impact. This makes it difficult to assess if small changes, such as the move to a new hardware architecture, will significantly affect a weather and climate model. We present a methodology that allows to objectively verify this. The methodology is applied to several test cases, showing a high sensitivity. Results also show that a major system update of the underlying supercomputer did not significantly affect our model.
Tom Kimpson, Margarita Choulga, Matthew Chantry, Gianpaolo Balsamo, Souhail Boussetta, Peter Dueben, and Tim Palmer
Hydrol. Earth Syst. Sci., 27, 4661–4685, https://doi.org/10.5194/hess-27-4661-2023, https://doi.org/10.5194/hess-27-4661-2023, 2023
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Lakes play an important role when we try to explain and predict the weather. More accurate and up-to-date description of lakes all around the world for numerical models is a continuous task. However, it is difficult to assess the impact of updated lake description within a weather prediction system. In this work, we develop a method to quickly and automatically define how, where, and when updated lake description affects weather prediction.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
EGUsphere, https://doi.org/10.5194/egusphere-2023-2263, https://doi.org/10.5194/egusphere-2023-2263, 2023
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We investigate the effects of reduced precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced precision implementations of their model.
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Weather Clim. Dynam., 4, 905–926, https://doi.org/10.5194/wcd-4-905-2023, https://doi.org/10.5194/wcd-4-905-2023, 2023
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Our study focuses on severe convective storms that occur over the Alpine-Adriatic region. By running simulations for eight real cases and evaluating them against available observations, we found our models did a good job of simulating total precipitation, hail, and lightning. Overall, this research identified important meteorological factors for hail and lightning, and the results indicate that both HAILCAST and LPI diagnostics are promising candidates for future climate research.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Roman Brogli, Christoph Heim, Jonas Mensch, Silje Lund Sørland, and Christoph Schär
Geosci. Model Dev., 16, 907–926, https://doi.org/10.5194/gmd-16-907-2023, https://doi.org/10.5194/gmd-16-907-2023, 2023
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The pseudo-global-warming (PGW) approach is a downscaling methodology that imposes the large-scale GCM-based climate change signal on the boundary conditions of a regional climate simulation. It offers several benefits in comparison to conventional downscaling. We present a detailed description of the methodology, provide companion software to facilitate the preparation of PGW simulations, and present validation and sensitivity studies.
Qinggang Gao, Christian Zeman, Jesus Vergara-Temprado, Daniela C. A. Lima, Peter Molnar, and Christoph Schär
Weather Clim. Dynam., 4, 189–211, https://doi.org/10.5194/wcd-4-189-2023, https://doi.org/10.5194/wcd-4-189-2023, 2023
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We developed a vortex identification algorithm for realistic atmospheric simulations. The algorithm enabled us to obtain a climatology of vortex shedding from Madeira Island for a 10-year simulation period. This first objective climatological analysis of vortex streets shows consistency with observed atmospheric conditions. The analysis shows a pronounced annual cycle with an increasing vortex shedding rate from April to August and a sudden decrease in September.
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Geosci. Model Dev., 15, 6817–6840, https://doi.org/10.5194/gmd-15-6817-2022, https://doi.org/10.5194/gmd-15-6817-2022, 2022
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Terrain horizon and sky view factor are crucial quantities for many geoscientific applications; e.g. they are used to account for effects of terrain on surface radiation in climate and land surface models. Because typical terrain horizon algorithms are inefficient for high-resolution (< 30 m) elevation data, we developed a new algorithm based on a ray-tracing library. A comparison with two conventional methods revealed both its high performance and its accuracy for complex terrain.
Christian Zeman and Christoph Schär
Geosci. Model Dev., 15, 3183–3203, https://doi.org/10.5194/gmd-15-3183-2022, https://doi.org/10.5194/gmd-15-3183-2022, 2022
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Our atmosphere is a chaotic system, where even a tiny change can have a big impact. This makes it difficult to assess if small changes, such as the move to a new hardware architecture, will significantly affect a weather and climate model. We present a methodology that allows to objectively verify this. The methodology is applied to several test cases, showing a high sensitivity. Results also show that a major system update of the underlying supercomputer did not significantly affect our model.
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
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Roman Brogli, Silje Lund Sørland, Nico Kröner, and Christoph Schär
Weather Clim. Dynam., 2, 1093–1110, https://doi.org/10.5194/wcd-2-1093-2021, https://doi.org/10.5194/wcd-2-1093-2021, 2021
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In a warmer future climate, climate simulations predict that some land areas will experience excessive warming during summer. We show that the excessive summer warming is related to the vertical distribution of warming within the atmosphere. In regions characterized by excessive warming, much of the warming occurs close to the surface. In other regions, most of the warming is redistributed to higher levels in the atmosphere, which weakens the surface warming.
Daniel Regenass, Linda Schlemmer, Elena Jahr, and Christoph Schär
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-426, https://doi.org/10.5194/hess-2021-426, 2021
Manuscript not accepted for further review
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Weather and climate models need to represent the water cycle on land in order to provide accurate estimates of moisture and energy exchange between the land and the atmosphere. Infiltration of water into the soil is often modeled with an equation describing water transport in porous media. Here, we point out some challenges arising in the numerical solution of this equation and show the consequences for the representation of the water cycle in modern weather and climate models.
Silje Lund Sørland, Roman Brogli, Praveen Kumar Pothapakula, Emmanuele Russo, Jonas Van de Walle, Bodo Ahrens, Ivonne Anders, Edoardo Bucchignani, Edouard L. Davin, Marie-Estelle Demory, Alessandro Dosio, Hendrik Feldmann, Barbara Früh, Beate Geyer, Klaus Keuler, Donghyun Lee, Delei Li, Nicole P. M. van Lipzig, Seung-Ki Min, Hans-Jürgen Panitz, Burkhardt Rockel, Christoph Schär, Christian Steger, and Wim Thiery
Geosci. Model Dev., 14, 5125–5154, https://doi.org/10.5194/gmd-14-5125-2021, https://doi.org/10.5194/gmd-14-5125-2021, 2021
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We review the contribution from the CLM-Community to regional climate projections following the CORDEX framework over Europe, South Asia, East Asia, Australasia, and Africa. How the model configuration, horizontal and vertical resolutions, and choice of driving data influence the model results for the five domains is assessed, with the purpose of aiding the planning and design of regional climate simulations in the future.
Jérôme Barré, Ilse Aben, Anna Agustí-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Peter Dueben, Richard Engelen, Antje Inness, Alba Lorente, Joe McNorton, Vincent-Henri Peuch, Gabor Radnoti, and Roberto Ribas
Atmos. Chem. Phys., 21, 5117–5136, https://doi.org/10.5194/acp-21-5117-2021, https://doi.org/10.5194/acp-21-5117-2021, 2021
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This study presents a new approach to the systematic global detection of anomalous local CH4 concentration anomalies caused by rapid changes in anthropogenic emission levels. The approach utilises both satellite measurements and model simulations, and applies novel data analysis techniques (such as filtering and classification) to automatically detect anomalous emissions from point sources and small areas, such as oil and gas drilling sites, pipelines and facility leaks.
Jun-Ichi Yano and Nils P. Wedi
Atmos. Chem. Phys., 21, 4759–4778, https://doi.org/10.5194/acp-21-4759-2021, https://doi.org/10.5194/acp-21-4759-2021, 2021
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Sensitivities of forecasts of the Madden–Julian oscillation (MJO) to various different configurations of the physics are examined with the global model of ECMWF's Integrated Forecasting System (IFS). The motivation for the study was to simulate the MJO as a nonlinear free wave. To emulate free dynamics in the IFS,
various momentum dissipation terms (
friction) as well as diabatic heating were selectively turned off over the tropics for the range of the latitudes from 20° S to 20° N.
Marie-Estelle Demory, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Erasmo Buonomo, Ole B. Christensen, James M. Ciarlo ̀, Rowan Fealy, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Retish Senan, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, https://doi.org/10.5194/gmd-13-5485-2020, 2020
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Now that global climate models (GCMs) can run at similar resolutions to regional climate models (RCMs), one may wonder whether GCMs and RCMs provide similar regional climate information. We perform an evaluation for daily precipitation distribution in PRIMAVERA GCMs (25–50 km resolution) and CORDEX RCMs (12–50 km resolution) over Europe. We show that PRIMAVERA and CORDEX simulate similar distributions. Considering both datasets at such a resolution results in large benefits for impact studies.
Stefan Rüdisühli, Michael Sprenger, David Leutwyler, Christoph Schär, and Heini Wernli
Weather Clim. Dynam., 1, 675–699, https://doi.org/10.5194/wcd-1-675-2020, https://doi.org/10.5194/wcd-1-675-2020, 2020
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Most precipitation over Europe is linked to low-pressure systems, cold fronts, warm fronts, or high-pressure systems. Based on a massive computer simulation able to resolve thunderstorms, we quantify in detail how much precipitation these weather systems produced during 2000–2008. We find distinct seasonal and regional differences, such as fronts precipitating a lot in fall and winter over the North Atlantic but high-pressure systems mostly in summer over the continent by way of thunderstorms.
Andreas Müller, Willem Deconinck, Christian Kühnlein, Gianmarco Mengaldo, Michael Lange, Nils Wedi, Peter Bauer, Piotr K. Smolarkiewicz, Michail Diamantakis, Sarah-Jane Lock, Mats Hamrud, Sami Saarinen, George Mozdzynski, Daniel Thiemert, Michael Glinton, Pierre Bénard, Fabrice Voitus, Charles Colavolpe, Philippe Marguinaud, Yongjun Zheng, Joris Van Bever, Daan Degrauwe, Geert Smet, Piet Termonia, Kristian P. Nielsen, Bent H. Sass, Jacob W. Poulsen, Per Berg, Carlos Osuna, Oliver Fuhrer, Valentin Clement, Michael Baldauf, Mike Gillard, Joanna Szmelter, Enda O'Brien, Alastair McKinstry, Oisín Robinson, Parijat Shukla, Michael Lysaght, Michał Kulczewski, Milosz Ciznicki, Wojciech Piątek, Sebastian Ciesielski, Marek Błażewicz, Krzysztof Kurowski, Marcin Procyk, Pawel Spychala, Bartosz Bosak, Zbigniew P. Piotrowski, Andrzej Wyszogrodzki, Erwan Raffin, Cyril Mazauric, David Guibert, Louis Douriez, Xavier Vigouroux, Alan Gray, Peter Messmer, Alexander J. Macfaden, and Nick New
Geosci. Model Dev., 12, 4425–4441, https://doi.org/10.5194/gmd-12-4425-2019, https://doi.org/10.5194/gmd-12-4425-2019, 2019
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This paper presents an overview of the ESCAPE project. Dwarfs (key patterns in terms of computation and communication) are identified in weather prediction models. They are optimised for different hardware architectures. New algorithms are developed that are specifically designed for better energy efficiency and improved portability through domain-specific languages. Different numerical techniques are compared in terms of energy efficiency and performance for a variety of computing technologies.
Margarita Choulga, Ekaterina Kourzeneva, Gianpaolo Balsamo, Souhail Boussetta, and Nils Wedi
Hydrol. Earth Syst. Sci., 23, 4051–4076, https://doi.org/10.5194/hess-23-4051-2019, https://doi.org/10.5194/hess-23-4051-2019, 2019
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Lakes influence weather and climate of regions, especially if several of them are located close by. Just by using upgraded lake depths, based on new or more recent measurements and geological methods of depth estimation, errors of lake surface water forecasts produced by the European Centre for Medium-Range Weather Forecasts became 12–20 % lower compared with observations for 27 lakes collected by the Finnish Environment Institute. For ice-off date forecasts errors changed insignificantly.
Christian Kühnlein, Willem Deconinck, Rupert Klein, Sylvie Malardel, Zbigniew P. Piotrowski, Piotr K. Smolarkiewicz, Joanna Szmelter, and Nils P. Wedi
Geosci. Model Dev., 12, 651–676, https://doi.org/10.5194/gmd-12-651-2019, https://doi.org/10.5194/gmd-12-651-2019, 2019
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We present a novel finite-volume dynamical core formulation considered for future numerical weather prediction at ECMWF. We demonstrate that this formulation can be competitive in terms of solution quality and computational efficiency to the proven spectral-transform dynamical core formulation currently operational at ECMWF, while providing a local, more scalable discretization, conservative and monotone advective transport, and flexible meshes.
Samuel Monhart, Massimiliano Zappa, Christoph Spirig, Christoph Schär, and Konrad Bogner
Hydrol. Earth Syst. Sci., 23, 493–513, https://doi.org/10.5194/hess-23-493-2019, https://doi.org/10.5194/hess-23-493-2019, 2019
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Subseasonal streamflow forecasts have received increasing attention during the past decade, but their performance in alpine catchments is still largely unknown. We analyse the effect of a statistical correction technique applied to the driving meteorological forecasts on the performance of the resulting streamflow forecasts. The study shows the benefits of such hydrometeorological ensemble prediction systems and highlights the importance of snow-related processes for subseasonal predictions.
Peter D. Dueben and Peter Bauer
Geosci. Model Dev., 11, 3999–4009, https://doi.org/10.5194/gmd-11-3999-2018, https://doi.org/10.5194/gmd-11-3999-2018, 2018
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We discuss the question of whether weather forecast models that are based on deep learning and trained on atmospheric data can compete with conventional weather and climate models that are based on physical principles and the basic equations of motion. We discuss the question in the context of global weather forecasts. A toy model for global weather predictions will be presented and used to identify challenges and fundamental design choices for a forecast system based on neural networks.
Stefan Brönnimann, Jan Rajczak, Erich M. Fischer, Christoph C. Raible, Marco Rohrer, and Christoph Schär
Nat. Hazards Earth Syst. Sci., 18, 2047–2056, https://doi.org/10.5194/nhess-18-2047-2018, https://doi.org/10.5194/nhess-18-2047-2018, 2018
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Heavy precipitation events in Switzerland are expected to become more intense, but the seasonality also changes. Analysing a large set of model simulations, we find that annual maximum rainfall events become less frequent in late summer and more frequent in early summer and early autumn. The seasonality shift is arguably related to summer drying. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events.
Erik Kjellström, Grigory Nikulin, Gustav Strandberg, Ole Bøssing Christensen, Daniela Jacob, Klaus Keuler, Geert Lenderink, Erik van Meijgaard, Christoph Schär, Samuel Somot, Silje Lund Sørland, Claas Teichmann, and Robert Vautard
Earth Syst. Dynam., 9, 459–478, https://doi.org/10.5194/esd-9-459-2018, https://doi.org/10.5194/esd-9-459-2018, 2018
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Based on high-resolution regional climate models we investigate European climate change at 1.5 and 2 °C of global warming compared to pre-industrial levels. Considerable near-surface warming exceeding that of the global mean is found for most of Europe, already at the lower 1.5 °C of warming level. Changes in precipitation and near-surface wind speed are identified. The 1.5 °C of warming level shows significantly less change compared to the 2 °C level, indicating the importance of mitigation.
Bryan N. Lawrence, Michael Rezny, Reinhard Budich, Peter Bauer, Jörg Behrens, Mick Carter, Willem Deconinck, Rupert Ford, Christopher Maynard, Steven Mullerworth, Carlos Osuna, Andrew Porter, Kim Serradell, Sophie Valcke, Nils Wedi, and Simon Wilson
Geosci. Model Dev., 11, 1799–1821, https://doi.org/10.5194/gmd-11-1799-2018, https://doi.org/10.5194/gmd-11-1799-2018, 2018
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Weather and climate models consist of complex software evolving in response to both scientific requirements and changing computing hardware. After years of relatively stable hardware, more diversity is arriving. It is possible that this hardware diversity and the pace of change may lead to an inability for modelling groups to manage their software development. This
chasmbetween aspiration and reality may need to be bridged by large community efforts rather than traditional
in-houseefforts.
Prisco Frei, Sven Kotlarski, Mark A. Liniger, and Christoph Schär
The Cryosphere, 12, 1–24, https://doi.org/10.5194/tc-12-1-2018, https://doi.org/10.5194/tc-12-1-2018, 2018
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Snowfall is central to Alpine environments, and its future changes will be associated with pronounced impacts. We here assess future snowfall changes in the European Alps based on an ensemble of state-of-the-art regional climate model experiments and on two different greenhouse gas emission scenarios. The results reveal pronounced changes in the Alpine snowfall climate with considerable snowfall reductions at low and mid-elevations but also snowfall increases at high elevations in midwinter.
Martin Wild, Atsumu Ohmura, Christoph Schär, Guido Müller, Doris Folini, Matthias Schwarz, Maria Zyta Hakuba, and Arturo Sanchez-Lorenzo
Earth Syst. Sci. Data, 9, 601–613, https://doi.org/10.5194/essd-9-601-2017, https://doi.org/10.5194/essd-9-601-2017, 2017
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The Global Energy Balance Archive (GEBA) is a database for the central storage of worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 database, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and to date contains around 500 000 monthly mean entries from 2500 locations.
Andrew Dawson and Peter D. Düben
Geosci. Model Dev., 10, 2221–2230, https://doi.org/10.5194/gmd-10-2221-2017, https://doi.org/10.5194/gmd-10-2221-2017, 2017
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Weather and climate models must become more efficient if they continue growing in complexity. One option for reducing computational cost is to reduce numerical precision. We present a tool that allows users to study how models perform with reduced numerical precision. The tool is applied to a geophysical use case where precision is heavily reduced while maintaining suitable accuracy. The tool can be applied to other models to determine whether they can be made more computationally efficient.
David Leutwyler, Oliver Fuhrer, Xavier Lapillonne, Daniel Lüthi, and Christoph Schär
Geosci. Model Dev., 9, 3393–3412, https://doi.org/10.5194/gmd-9-3393-2016, https://doi.org/10.5194/gmd-9-3393-2016, 2016
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The representation of moist convection (thunderstorms and rain showers) in climate models represents a major challenge, as this process is usually approximated due to the lack of appropriate computational resolution. Climate simulations using horizontal resolution of O(1 km) allow one to explicitly resolve deep convection and thus allow for an improved representation of the water cycle. We present a set of such simulations covering the European scale using a climate model enabled for GPUs.
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
S. Kotlarski, K. Keuler, O. B. Christensen, A. Colette, M. Déqué, A. Gobiet, K. Goergen, D. Jacob, D. Lüthi, E. van Meijgaard, G. Nikulin, C. Schär, C. Teichmann, R. Vautard, K. Warrach-Sagi, and V. Wulfmeyer
Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, https://doi.org/10.5194/gmd-7-1297-2014, 2014
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The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 1: Understanding expressiveness of schemes for different regions from the mechanism perspective
Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data
The capabilities of the adjoint of GEOS-Chem model to support HEMCO emission inventories and MERRA-2 meteorological data
Rapid O3 assimilations – Part 1: Background and local contributions to tropospheric O3 changes in China in 2015–2020
Description and evaluation of the new UM–UKCA (vn11.0) Double Extended Stratospheric–Tropospheric (DEST vn1.0) scheme for comprehensive modelling of halogen chemistry in the stratosphere
A robust error correction method for numerical weather prediction wind speed based on Bayesian optimization, variational mode decomposition, principal component analysis, and random forest: VMD-PCA-RF (version 1.0.0)
Description and performance of a sectional aerosol microphysical model in the Community Earth System Model (CESM2)
A simplified non-linear chemistry transport model for analyzing NO2 column observations: STILT–NOx
The Hydro-ABC model (Version 2.0): a simplified convective-scale model with moist dynamics
Rapid Adaptive Optimization Model for Atmospheric Chemistry (ROMAC) v1.0
A standardized methodology for the validation of air quality forecast applications (F-MQO): lessons learnt from its application across Europe
Application of the Multi-Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0) for air quality research in Africa
A Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) for emission estimates: system development and application
Evaluation of vertically resolved longwave radiation in SPARTACUS-Urban 0.7.3 and the sensitivity to urban surface temperatures
Key factors for quantitative precipitation nowcasting using ground weather radar data based on deep learning
An Overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
QES-Plume v1.0: a Lagrangian dispersion model
A two-way coupled regional urban–street network air quality model system for Beijing, China
Simulations of idealised 3D atmospheric flows on terrestrial planets using LFRic-Atmosphere
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
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The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
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We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
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The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Leonardo Olivetti and Gabriele Messori
EGUsphere, https://doi.org/10.5194/egusphere-2023-2490, https://doi.org/10.5194/egusphere-2023-2490, 2023
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In recent years, deep learning models have emerged as a data-driven alternative to physics-based models for medium-range weather forecasting. This article provides an overview of recent developments in the field, and explores the challenges that deep learning models face when considering extreme weather events. It argues for the need to complement current approaches with models specifically designed to handle extreme events, and proposes a foundational framework to develop such models.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
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Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
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This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, https://doi.org/10.5194/gmd-16-6635-2023, 2023
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Most current studies on planetary boundary layer (PBL) parameterization schemes are relatively fragmented and lack systematic in-depth analysis and discussion. In this study, we comprehensively evaluate the performance capability of the PBL scheme in five typical regions of China in different seasons from the mechanism of the scheme and the effects of PBL schemes on the near-surface meteorological parameters, vertical structures of the PBL, PBL height, and turbulent diffusion.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev., 16, 6531–6552, https://doi.org/10.5194/gmd-16-6531-2023, https://doi.org/10.5194/gmd-16-6531-2023, 2023
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It is important to know how well atmospheric models do in mountains, but there are not very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado River basin against the available data. The model works rather well, but there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we could not do before.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
EGUsphere, https://doi.org/10.5194/egusphere-2023-2587, https://doi.org/10.5194/egusphere-2023-2587, 2023
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation we find that MESSy’s bias in modelling routinely observed inorganic aerosol mass concentrations is reduced. Furthermore, the representation of fine aerosol pH is particularly improved in the marine boundary layer.
Angel Liduvino Vara-Vela, Christoffer Karoff, Noelia Rojas Benavente, and Janaina P. Nascimento
Geosci. Model Dev., 16, 6413–6431, https://doi.org/10.5194/gmd-16-6413-2023, https://doi.org/10.5194/gmd-16-6413-2023, 2023
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A 1-year simulation of atmospheric CH4 over Europe is performed and evaluated against observations based on the TROPOspheric Monitoring Instrument (TROPOMI). A good general model–observation agreement is found, with discrepancies reaching their minimum and maximum values during the summer peak season and winter months, respectively. A huge and under-explored potential for CH4 inverse modeling using improved TROPOMI XCH4 data sets in large-scale applications is identified.
Zhaojun Tang, Zhe Jiang, Jiaqi Chen, Panpan Yang, and Yanan Shen
Geosci. Model Dev., 16, 6377–6392, https://doi.org/10.5194/gmd-16-6377-2023, https://doi.org/10.5194/gmd-16-6377-2023, 2023
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We designed a new framework to facilitate emission inventory updates in the adjoint of GEOS-Chem model. It allows us to support Harmonized Emissions Component (HEMCO) emission inventories conveniently and to easily add more emission inventories following future updates in GEOS-Chem forward simulations. Furthermore, we developed new modules to support MERRA-2 meteorological data; this allows us to perform long-term analysis with consistent meteorological data.
Rui Zhu, Zhaojun Tang, Xiaokang Chen, Xiong Liu, and Zhe Jiang
Geosci. Model Dev., 16, 6337–6354, https://doi.org/10.5194/gmd-16-6337-2023, https://doi.org/10.5194/gmd-16-6337-2023, 2023
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A single ozone (O3) tracer mode was developed in this work to build the capability of the GEOS-Chem model for rapid O3 simulation. It is combined with OMI and surface O3 observations to investigate the changes in tropospheric O3 in China in 2015–2020. The assimilations indicate rapid surface O3 increases that are underestimated by the a priori simulations. We find stronger increases in tropospheric O3 columns over polluted areas and a large discrepancy by assimilating different observations.
Ewa M. Bednarz, Ryan Hossaini, N. Luke Abraham, and Martyn P. Chipperfield
Geosci. Model Dev., 16, 6187–6209, https://doi.org/10.5194/gmd-16-6187-2023, https://doi.org/10.5194/gmd-16-6187-2023, 2023
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Development and performance of the new DEST chemistry scheme of UM–UKCA is described. The scheme extends the standard StratTrop scheme by including important updates to the halogen chemistry, thus allowing process-oriented studies of stratospheric ozone depletion and recovery, including impacts from both controlled long-lived ozone-depleting substances and emerging issues around uncontrolled, very short-lived substances. It will thus aid studies in support of future ozone assessment reports.
Shaohui Zhou, Chloe Yuchao Gao, Zexia Duan, Xingya Xi, and Yubin Li
Geosci. Model Dev., 16, 6247–6266, https://doi.org/10.5194/gmd-16-6247-2023, https://doi.org/10.5194/gmd-16-6247-2023, 2023
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The proposed wind speed correction model (VMD-PCA-RF) demonstrates the highest prediction accuracy and stability in the five southern provinces in nearly a year and at different heights. VMD-PCA-RF evaluation indices for 13 months remain relatively stable: the forecasting accuracy rate FA is above 85 %. In future research, the proposed VMD-PCA-RF algorithm can be extrapolated to the 3 km grid points of the five southern provinces to generate a 3 km grid-corrected wind speed product.
Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, and Terry Deshler
Geosci. Model Dev., 16, 6087–6125, https://doi.org/10.5194/gmd-16-6087-2023, https://doi.org/10.5194/gmd-16-6087-2023, 2023
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We implemented an alternative aerosol scheme in the high- and low-top model versions of the Community Earth System Model Version 2 (CESM2) with a more detailed description of tropospheric and stratospheric aerosol size distributions than the existing aerosol model. This development enables the comparison of different aerosol schemes with different complexity in the same model framework. It identifies improvements compared to a range of observations in both the troposphere and stratosphere.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
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To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Jiangshan Zhu and Ross Noel Bannister
Geosci. Model Dev., 16, 6067–6085, https://doi.org/10.5194/gmd-16-6067-2023, https://doi.org/10.5194/gmd-16-6067-2023, 2023
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We describe how condensation and evaporation are included in the existing (otherwise dry) simplified ABC model. The new model (Hydro-ABC) includes transport of vapour and condensate within a dynamical core, and it transitions between these two phases via a micro-physics scheme. The model shows the development of an anvil cloud and excitation of atmospheric waves over many frequencies. The covariances that develop between variables are also studied together with indicators of convective motion.
Jiangyong Li, Chunlin Zhang, Wenlong Zhao, Shijie Han, Yu Wang, Hao Wang, and Boguang Wang
Geosci. Model Dev., 16, 6049–6066, https://doi.org/10.5194/gmd-16-6049-2023, https://doi.org/10.5194/gmd-16-6049-2023, 2023
Short summary
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Photochemical box models, crucial for understanding tropospheric chemistry, face challenges due to slow computational efficiency with large chemical equations. The model introduced in this study, ROMAC, boosts efficiency by up to 96 % using an advanced atmospheric solver and an adaptive optimization algorithm. Moreover, ROMAC exceeds traditional box models in evaluating the impact of physical processes on pollutant concentrations.
Lina Vitali, Kees Cuvelier, Antonio Piersanti, Alexandra Monteiro, Mario Adani, Roberta Amorati, Agnieszka Bartocha, Alessandro D'Ausilio, Paweł Durka, Carla Gama, Giulia Giovannini, Stijn Janssen, Tomasz Przybyła, Michele Stortini, Stijn Vranckx, and Philippe Thunis
Geosci. Model Dev., 16, 6029–6047, https://doi.org/10.5194/gmd-16-6029-2023, https://doi.org/10.5194/gmd-16-6029-2023, 2023
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Air quality forecasting models play a key role in fostering short-term measures aimed at reducing human exposure to air pollution. Together with this role comes the need for a thorough assessment of the model performances to build confidence in models’ capabilities, in particular when model applications support policymaking. In this paper, we propose an evaluation methodology and test it on several domains across Europe, highlighting its strengths and room for improvement.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce C. Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev., 16, 6001–6028, https://doi.org/10.5194/gmd-16-6001-2023, https://doi.org/10.5194/gmd-16-6001-2023, 2023
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The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model–satellite discrepancies, we find that future field campaigns in an eastern African region (30°E–45°E, 5°S–5°N) could substantially improve the predictive skill of air quality models.
Shuzhuang Feng, Fei Jiang, Zheng Wu, Hengmao Wang, Wei He, Yang Shen, Lingyu Zhang, Yanhua Zheng, Chenxi Lou, Ziqiang Jiang, and Weimin Ju
Geosci. Model Dev., 16, 5949–5977, https://doi.org/10.5194/gmd-16-5949-2023, https://doi.org/10.5194/gmd-16-5949-2023, 2023
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We document the system development and application of a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0). This system is developed to optimize gridded source emissions of CO, SO2, NOx, primary PM2.5, and coarse PM10 on a regional scale via simultaneously assimilating surface measurements of CO, SO2, NO2, PM2.5, and PM10. A series of sensitivity experiments demonstrates the advantage of the “two-step” inversion strategy and the robustness of the system in estimating the emissions.
Megan A. Stretton, William Morrison, Robin J. Hogan, and Sue Grimmond
Geosci. Model Dev., 16, 5931–5947, https://doi.org/10.5194/gmd-16-5931-2023, https://doi.org/10.5194/gmd-16-5931-2023, 2023
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Cities' materials and forms impact radiative fluxes. We evaluate the SPARTACUS-Urban multi-layer approach to modelling longwave radiation, describing realistic 3D geometry statistically using the explicit DART (Discrete Anisotropic Radiative Transfer) model. The temperature configurations used are derived from thermal camera observations. SPARTACUS-Urban accurately predicts longwave fluxes, with a low computational time (cf. DART), but has larger errors with sunlit/shaded surface temperatures.
Daehyeon Han, Jungho Im, Yeji Shin, and Juhyun Lee
Geosci. Model Dev., 16, 5895–5914, https://doi.org/10.5194/gmd-16-5895-2023, https://doi.org/10.5194/gmd-16-5895-2023, 2023
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To identify the key factors affecting quantitative precipitation nowcasting (QPN) using deep learning (DL), we carried out a comprehensive evaluation and analysis. We compared four key factors: DL model, length of the input sequence, loss function, and ensemble approach. Generally, U-Net outperformed ConvLSTM. Loss function and ensemble showed potential for improving performance when they synergized well. The length of the input sequence did not significantly affect the results.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary Lebo, Emily Slinskey, and the UCLA Center for Climate Science Team
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-162, https://doi.org/10.5194/gmd-2023-162, 2023
Revised manuscript accepted for GMD
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically-based ensemble of climate data for use at local scales. Strengths and weakness of the data are frankly discussed as we overview the downscaled dataset.
Fabien Margairaz, Balwinder Singh, Jeremy A. Gibbs, Loren Atwood, Eric R. Pardyjak, and Rob Stoll
Geosci. Model Dev., 16, 5729–5754, https://doi.org/10.5194/gmd-16-5729-2023, https://doi.org/10.5194/gmd-16-5729-2023, 2023
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The Quick Environmental Simulation (QES) tool is a low-computational-cost fast-response framework. It provides high-resolution wind and concentration information to study complex problems, such as spore or smoke transport, urban pollution, and air quality. This paper presents the particle dispersion model and its validation against analytical solutions and wind-tunnel data for a mock-urban setting. In all cases, the model provides accurate results with competitive computational performance.
Tao Wang, Hang Liu, Jie Li, Shuai Wang, Youngseob Kim, Yele Sun, Wenyi Yang, Huiyun Du, Zhe Wang, and Zifa Wang
Geosci. Model Dev., 16, 5585–5599, https://doi.org/10.5194/gmd-16-5585-2023, https://doi.org/10.5194/gmd-16-5585-2023, 2023
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This paper developed a two-way coupled module in a new version of a regional urban–street network model, IAQMS-street v2.0, in which the mass flux from streets to background is considered. Test cases are defined to evaluate the performance of IAQMS-street v2.0 in Beijing by comparing it with that simulated by IAQMS-street v1.0 and a regional model. The contribution of local emissions and the influence of on-road vehicle control measures on air quality are evaluated by using IAQMS-street v2.0.
Denis E. Sergeev, Nathan J. Mayne, Thomas Bendall, Ian A. Boutle, Alex Brown, Iva Kavčič, James Kent, Krisztian Kohary, James Manners, Thomas Melvin, Enrico Olivier, Lokesh K. Ragta, Ben Shipway, Jon Wakelin, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 16, 5601–5626, https://doi.org/10.5194/gmd-16-5601-2023, https://doi.org/10.5194/gmd-16-5601-2023, 2023
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Three-dimensional climate models are one of the best tools we have to study planetary atmospheres. Here, we apply LFRic-Atmosphere, a new model developed by the Met Office, to seven different scenarios for terrestrial planetary climates, including four for the exoplanet TRAPPIST-1e, a primary target for future observations. LFRic-Atmosphere reproduces these scenarios within the spread of the existing models across a range of key climatic variables, justifying its use in future exoplanet studies.
Cited articles
Bacmeister, J. T., Eckermann, S. D., Newman, P. A., Lait, L., Chan, R. K.,
Loewenstein, M., Proffitt, M. H., and Gary, B. L.: Stratospheric horizontal
wavenumber spectra of winds, potential temperature, and atmospheric tracers
observed by high-altitude aircraft, J. Geophys. Res.-Atmos., 101, 9441–9470, https://doi.org/10.1029/95JD03835, 1996. a
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M.,
and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction
with the COSMO Model: Description and Sensitivities, Mon. Weather Rev.,
139, 3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011. a, b
Balsamo, G., Pappenberger, F., Dutra, E., Viterbo, P., and van den Hurk, B.: A
revised land hydrology in the ECMWF model: a step towards daily water flux
prediction in a fully-closed water cycle, Hydrol. Process., 25,
1046–1054, https://doi.org/10.1002/hyp.7808, 2011. a
Ban, N., Schmidli, J., and Schär, C.: Evaluation of the
convection-resolving regional climate modeling approach in decade-long
simulations, J. Geophys. Res.-Atmos., 119, 7889–7907,
https://doi.org/10.1002/2014JD021478, 2014. a, b, c, d
Barker, H. W., Cole, J. N. S., Morcrette, J.-J., Pincus, R.,
Räisänen, P., von Salzen, K., and Vaillancourt, P. A.: The Monte
Carlo Independent Column Approximation: an assessment using several global
atmospheric models, Q. J. Roy. Meteor. Soc.,
134, 1463–1478, https://doi.org/10.1002/qj.303, 2008. a
Barrett, A. I., Wellmann, C., Seifert, A., Hoose, C., Vogel, B., and Kunz, M.:
One Step at a Time: How Model Time Step Significantly Affects
Convection-Permitting Simulations, J. Adv. Model. Earth
Sy., 11, 641–658, https://doi.org/10.1029/2018MS001418, 2019. a, b, c
Bartels, H., Weigl, E., Reich, T., Lang, P., Wagner, A., Kohler, O., Gerlach,
N., and MeteoSolutions GmbH: Projekt RADOLAN – Routineverfahren zur
Online-Aneichung der Radarniederschlagsdaten mit Hilfe von automatischen
Bodenniederschlagsstationen (Ombrometer), Tech. rep., Deutscher
Wetterdienst, Hydrometeorologie,
available at: https://www.dwd.de/DE/leistungen/radolan/radolan_info/abschlussbericht_pdf.pdf?__blob=publicationFile&v=2 (last access: 13 July 2021),
2004. a
Bechtold, P., Köhler, M., Jung, T., Doblas-Reyes, F., Leutbecher, M.,
Rodwell, M. J., Vitart, F., and Balsamo, G.: Advances in simulating
atmospheric variability with the ECMWF model: From synoptic to decadal
time-scales, Q. J. Roy. Meteor. Soc., 134,
1337–1351, https://doi.org/10.1002/qj.289, 2008. a
Bechtold, P., Semane, N., Lopez, P., Chaboureau, J. P., Beljaars, A., and
Bormann, N.: Representing equilibrium and nonequilibrium convection in
large-scale models, J. Atmos. Sci., 71, 734–753,
https://doi.org/10.1175/JAS-D-13-0163.1, 2014. a, b, c
Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., Schamm, K., Schneider, U., and Ziese, M.: A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present, Earth Syst. Sci. Data, 5, 71–99, https://doi.org/10.5194/essd-5-71-2013, 2013. a
Bénard, P., Vivoda, J., Mascaronek, J., Smolíková, P.,
Yessad, K., Smith, C., Brožková, R., and Geleyn, J. F.:
Dynamical kernel of the Aladin-NH spectral limited-area model: Revised
formulation and sensitivity experiments, Q. J. Roy. Meteor. Soc., 136, 155–169, https://doi.org/10.1002/qj.522, 2010. a
Betts, A. K. and Jakob, C.: Study of diurnal cycle of convective precipitation
over Amazonia using a single column model, J. Geophys. Res.-Atmos., 107, ACL 25-1–ACL 25-13, https://doi.org/10.1029/2002JD002264, 2002. a
Bonaventura, L.: An introduction to semi-Lagrangian methods for geophysical
scale flows, Lecture Notes, ERCOFTAC Leonhard Euler Lectures, SAM-ETH
Zurich, Zurich, 2004. a
Bryan, G. H., Wyngaard, J. C., and Fritsch, J. M.: Resolution Requirements for
the Simulation of Deep Moist Convection, Mon. Weather Rev., 131,
2394–2416, https://doi.org/10.1175/1520-0493(2003)131<2394:RRFTSO>2.0.CO;2, 2003. a
Bubnová, R., Hello, G., Bénard, P., and Geleyn, J.-F.: Integration
of the Fully Elastic Equations Cast in the Hydrostatic Pressure
Terrain-Following Coordinate in the Framework of the ARPEGE/Aladin NWP
System, Mon. Weather Rev., 123, 515–535,
https://doi.org/10.1175/1520-0493(1995)123<0515:IOTFEE>2.0.CO;2, 1995. a
Callies, J., Bühler, O., and Ferrari, R.: The dynamics of mesoscale
winds in the upper troposphere and lower stratosphere, J.
Atmos. Sci., 73, 4853–4872, https://doi.org/10.1175/JAS-D-16-0108.1, 2016. a
Cho, J. Y., Zhu, Y., Newell, R. E., Anderson, B. E., Barrick, J. D., Gregory,
G. L., Sachse, G. W., Carroll, M. A., and Albercook, G. M.: Horizontal
wavenumber spectra of winds, temperature, and trace gases during the Pacific
Exploratory Missions: 1. Climatology, J. Geophys. Res.-Atmos., 104, 5697–5716, https://doi.org/10.1029/98JD01825, 1999a. a
Cho, J. Y. N., Newell, R. E., and Barrick, J. D.: Horizontal wavenumber
spectra of winds, temperature, and trace gases during the Pacific Exploratory
Missions: 2. Gravity waves, quasi‐two‐dimensional turbulence, and
vortical modes, J. Geophys. Res., 104, 16297–16308,
https://doi.org/10.1029/1999JD900068, 1999b. a
Courant, R., Friedrichs, K., and Lewy, H.: Über die partiellen
Differenzengleichungen der mathematischen Physik, Mathematische Annalen,
100, 32–74, https://doi.org/10.1007/BF01448839, 1928. a
Dai, A. and Trenberth, K. E.: The diurnal cycle and its depiction in the
community climate system model, J. Climate, 17, 930–951,
https://doi.org/10.1175/1520-0442(2004)017<0930:TDCAID>2.0.CO;2, 2004. a, b
Daley, R.: The normal modes of the spherical non-hydrostatic equations with
applications to the filtering of acoustic modes normal modes of the spherical
non-hydrostatic equations with applications to the filterin, Tellus A, 40, 96–106,
https://doi.org/10.3402/tellusa.v40i2.11785, 1988. a
Dirmeyer, P. A., Cash, B. A., Kinter, J. L., Jung, T., Marx, L., Satoh, M.,
Stan, C., Tomita, H., Towers, P., Wedi, N., Achuthavarier, D., Adams, J. M.,
Altshuler, E. L., Huang, B., Jin, E. K., and Manganello, J.: Simulating the
diurnal cycle of rainfall in global climate models: Resolution versus
parameterization, Clim. Dynam., 39, 399–418,
https://doi.org/10.1007/s00382-011-1127-9, 2012. a
Doms, G. and Baldauf, M.: A Description of the Nonhydrostatic Regional
COSMO-Model Part I : Dynamics and Numerics,
https://doi.org/10.5676/DWD_pub/nwv/cosmo-doc_5.05_I, 2018. a, b
Done, J., Davis, C. A., and Weisman, M.: The next generation of NWP: Explicit
forecasts of convection using the weather research and forecasting (WRF)
model, Atmos. Sci. Lett., 5, 110–117, https://doi.org/10.1002/asl.72, 2004. a
Dudhia, J.: A nonhydrostatic version of the Penn State-NCAR mesoscale model:
validation tests and simulation of an Atlantic cyclone and cold front,
Mon. Weather Rev., 121, 1493–1513,
https://doi.org/10.1175/1520-0493(1993)121<1493:ANVOTP>2.0.CO;2, 1993. a
ECMWF: Part IV : Physical processes, in: IFS Documentation CY45R1, ECMWF, 4,
https://doi.org/10.21957/4whwo8jw0, 2018. a
Fosser, G., Khodayar, S., and Berg, P.: Benefit of convection permitting
climate model simulations in the representation of convective precipitation,
Clim. Dynam., 44, 45–60, https://doi.org/10.1007/s00382-014-2242-1, 2014. a
Fuhrer, O., Osuna, C., Lapillonne, X., Gysi, T., Bianco, M., Arteaga, A., and
Schulthess, T. C.: Towards a performance portable, architecture agnostic
implementation strategy for weather and climate models, Supercomputing
Frontiers and Innovations, 1, 44–61, https://doi.org/10.14529/jsfi140103, 2014. a
Fuhrer, O., Chadha, T., Hoefler, T., Kwasniewski, G., Lapillonne, X., Leutwyler, D., Lüthi, D., Osuna, C., Schär, C., Schulthess, T. C., and Vogt, H.: Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0, Geosci. Model Dev., 11, 1665–1681, https://doi.org/10.5194/gmd-11-1665-2018, 2018. a, b
Gao, X. and Meriwether, J. W.: Mesoscale spectral analysis of in situ
horizontal and vertical wind measurements at 6 km, J. Geophys. Res.-Atmos., 103, 6397–6404, https://doi.org/10.1029/97JD03074, 1998. a
Gelb, A. and Gleeson, J. P.: Spectral Viscosity for Shallow Water Equations in
Spherical Geometry, Mon. Weather Rev., 129, 2346–2360,
https://doi.org/10.1175/1520-0493(2001)129<2346:SVFSWE>2.0.CO;2, 2001. a
Guichard, F., Petch, J. C., Redelsperger, J. L., Bechtold, P., Chaboureau,
J. P., Cheinet, S., Grabowski, W., Grenier, H., Jones, C. G., Köhler,
M., Piriou, J. M., Tailleux, R., and Tomasini, M.: Modelling the diurnal
cycle of deep precipitating convection over land with cloud-resolving models
and single-column models, Q. J. Roy. Meteor. Soc., 130 C, 3139–3172, https://doi.org/10.1256/qj.03.145, 2004. a
Held, I. M. and Soden, B. J.: Robust responses of the Hydrological Cycle to
Global Warming, J. Climate, 19, 5686–5699,
https://doi.org/10.1175/JCLI3990.1, 2006. a
Hogan, R., Ahlgrimm, M., Balsamo, G., Beljaars, A., Berrisford, P., Bozzo, A.,
Giuseppe, F. D., Forbes, R. M., Haiden, T., Lang, S., Mayer, M.,
Polichtchouk, I., Sandu, I., Vitart, F., and Wedi, N.: Radiation in
numerical weather prediction, ECMWF Technical Memoranda, 816, 1–49,
https://doi.org/10.21957/2bd5dkj8x, 2017. a
Hohenegger, C., Brockhaus, P., and Schär, C.: Towards climate
simulations at cloud-resolving scales, Meteorol. Z., 17,
383–394, https://doi.org/10.1127/0941-2948/2008/0303, 2008. a, b
Houze, R. A. and Betts, A. K.: Convection in GATE, Rev. Geophys.
Space Phys., 19, 541–576,
https://doi.org/10.1029/RG019i004p00541, 1981. a
Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C.,
Nelkin, E. J., Sorooshian, S., Tan, J., and Xie, P.: NASA Global
Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM
(IMERG), Algorithm Theoretical Basis Document (ATBD) Version 06,
available at: https://gpm.nasa.gov/sites/default/files/2019-05/IMERG_ATBD_V06.pdf (last access: 13 July 2021),
2019a. a
Huffman, G. J., Stocker, E. F., Bolvin, D. T., Nelkin, E. J., and Jackson, T.:
GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree × 0.1 degree V06,
https://doi.org/10.5067/GPM/IMERG/3B-HH/06, 2019b. a
IDAWEB: IDAWEB, available at: https://gate.meteoswiss.ch/idaweb, last access: 15 January 2021. a
Jablonowski, C. and Williamson, D. L.: The Pros and Cons of Diffusion, Filters
and Fixers in Atmospheric General Circulation Models BT – Numerical
Techniques for Global Atmospheric Models, in: Numerical Techniques for
Global Atmospheric Models, edited by: Lauritzen, P., Jablonowski, C., Taylor,
M., and Nair, R., Springer Berlin Heidelberg, Berlin,
Heidelberg, 381–493, https://doi.org/10.1007/978-3-642-11640-7_13, 2011. a
Jeevanjee, N.: Vertical Velocity in the Gray Zone, J. Adv.
Model. Earth Syst., 9, 2304–2316, https://doi.org/10.1002/2017MS001059, 2017. a, b, c
Jung, T., Miller, M. J., Palmer, T. N., Towers, P., Wedi, N., Achuthavarier,
D., Adams, J. M., Altshuler, E. L., Cash, B. A., Kinter III, J. L., Marx, L.,
Stan, C., and Hodges, K. I.: High-Resolution Global Climate Simulations with
the ECMWF Model in Project Athena: Experimental Design, Model Climate, and
Seasonal Forecast Skill, J. Climate, 25, 3155–3172,
https://doi.org/10.1175/JCLI-D-11-00265.1, 2012. a
Kato, T.: Hydrostatic and Non-hydrostatic Simulations of the 6 August 1993
Kagoshima Torrential Rain, J. Meteorol. Soc. Japan
Ser. II, 74, 355–363, https://doi.org/10.2151/jmsj1965.74.3_355, 1996. a
Kato, T.: Hydrostatic and non-hydrostatic simulations of moist convection:
Review and further study, Meteorol. Atmos. Phys., 63, 39–51,
https://doi.org/10.1007/BF01025363, 1997. a, b, c
Kato, T. and Saito, K.: Hydrostatic and Non-Hydrostatic Simulations of Moist
Convection: Applicability of the Hydrostatic Approximation to a
High-Resolution Model, J. Meteorol. Soc. Japan, 73,
59–77, https://doi.org/10.2151/jmsj1965.73.1_59, 1995. a, b
Kendon, E. J., Roberts, N. M., Senior, C. A., and Roberts, M. J.: Realism of
rainfall in a very high-resolution regional climate model, J.
Climate, 25, 5791–5806, https://doi.org/10.1175/JCLI-D-11-00562.1, 2012. a
Kendon, E. J., Stratton, R. A., Tucker, S., Marsham, J. H., Berthou, S.,
Rowell, D. P., and Senior, C. A.: Enhanced future changes in wet and dry
extremes over Africa at convection-permitting scale, Nat. Commun.,
10, 1794, https://doi.org/10.1038/s41467-019-09776-9, 2019. a
Kühnlein, C., Deconinck, W., Klein, R., Malardel, S., Piotrowski, Z. P., Smolarkiewicz, P. K., Szmelter, J., and Wedi, N. P.: FVM 1.0: a nonhydrostatic finite-volume dynamical core for the IFS, Geosci. Model Dev., 12, 651–676, https://doi.org/10.5194/gmd-12-651-2019, 2019. a, b
Lafore, J. P., Stein, J., Asencio, N., Bougeault, P., Ducrocq, V., Duron, J., Fischer, C., Héreil, P., Mascart, P., Masson, V., Pinty, J. P., Redelsperger, J. L., Richard, E., and Vilà-Guerau de Arellano, J.: The Meso-NH Atmospheric Simulation System. Part I: adiabatic formulation and control simulations, Ann. Geophys., 16, 90–109, https://doi.org/10.1007/s00585-997-0090-6, 1998. a
Langhans, W., Schmidli, J., and Schär, C.: Bulk Convergence of
Cloud-Resolving Simulations of Moist Convection over Complex Terrain,
J. Atmos. Sci., 69, 2207–2228,
https://doi.org/10.1175/JAS-D-11-0252.1, 2012. a
Lauritzen, P. H., Jablonowski, C., Taylor, M. A., and Nair, R. D.: Numerical
techniques for global atmospheric models, vol. 80, Springer Science &
Business Media, 2011. a
Lebo, Z. J. and Morrison, H.: Effects of horizontal and vertical grid spacing
on mixing in simulated squall lines and implications for convective strength
and structure, Mon. Weather Rev., 143, 4355–4375,
https://doi.org/10.1175/MWR-D-15-0154.1, 2015. a
Legates, D. R. and Willmott, C. J.: Mean seasonal and spatial variability in
gauge‐corrected, global precipitation, Int. J.
Climatol., 10, 111–127, https://doi.org/10.1002/joc.3370100202,
1990. a, b
Leutwyler, D., Lüthi, D., Ban, N., Fuhrer, O., and Schär, C.:
Evaluation of the convection-resolving climate modeling approach on
continental scales, J. Geophys. Res., 122, 5237–5258,
https://doi.org/10.1002/2016JD026013, 2017. a, b, c
Lindborg, E.: Can the atmospheric kinetic energy spectrum be explained by
two-dimensional turbulence?, J. Fluid Mech., 388, 259–288,
https://doi.org/10.1017/S0022112099004851, 1999. a
Liu, H.-L.: Quantifying gravity wave forcing using scale invariance, Nat.
Commun., 10, 2605, https://doi.org/10.1038/s41467-019-10527-z, 2019. a
Lott, F. and Miller, M. J.: A new subgrid-scale orographic drag
parametrization: Its formulation and testing, Q. J. Roy.
Meteor. Soc., 123, 101–127, https://doi.org/10.1256/smsqj.53703, 1997. a
Malardel, S. and Ricard, D.: An alternative cell-averaged departure point
reconstruction for pointwise semi-Lagrangian transport schemes, Q. J. Roy. Meteor. Soc., 141, 2114–2126,
https://doi.org/10.1002/qj.2509, 2015. a, b, c
Malardel, S. and Wedi, N. P.: How does subgrid-scale parametrization influence
nonlinear spectral energy fluxes in global NWP models?, J.
Geophys. Res.-Atmos., 121, 5395–5410,
https://doi.org/10.1002/2015JD023970, 2016. a, b
Malardel, S., Wedi, N., Deconinck, W., Diamantakis, M., Kühnlein, C.,
Mozdzynski, G., Hamrud, M., and Smolarkiewicz, P.: A new grid for the IFS,
ECMWF Newsletter, 146, 23–28, https://doi.org/10.21957/zwdu9u5i, 2016. a
Manabe, S., Smagorinky, J., and Strickler, R. F.: Simulated Climatology of a
General Circulation Model With a Hydrologic Cycle 1, Mon. Weather Rev.,
93, 769–798, https://doi.org/10.1175/1520-0493(1965)093<0769:scoagc>2.3.co;2, 1965. a
Mishra, S. K. and Sahany, S.: Effects of time step size on the simulation of
tropical climate in NCAR-CAM3, Clim. Dynam., 37, 689–704,
https://doi.org/10.1007/s00382-011-0994-4, 2011. a
Miyamoto, Y., Kajikawa, Y., Yoshida, R., Yamaura, T., Yashiro, H., and Tomita,
H.: Deep moist atmospheric convection in a subkilometer global simulation,
Geophys. Res. Lett., 40, 4922–4926, https://doi.org/10.1002/grl.50944, 2013. a
Nastrom, G. D. and Gage, K. S.: A Climatology of Atmospheric Wavenumber
Spectra of Wind and Temperature Observed by Commercial Aircraft, J. Atmos. Sci., 42, 950–960,
https://doi.org/10.1175/1520-0469(1985)042<0950:ACOAWS>2.0.CO;2, 1985. a
Neumann, P., Düben, P., Adamidis, P., Bauer, P., Brück, M.,
Kornblueh, L., Klocke, D., Stevens, B., Wedi, N., and Biercamp, J.:
Assessing the scales in numerical weather and climate predictions: Will
exascale be the rescue?, Philos. T. Roy. Soc. A, 377, 20180148,
https://doi.org/10.1098/rsta.2018.0148, 2019. a
Orlanski, I.: The quasi-hydrostatic approximation., J.
Atmos. Sci., 38, 572–582,
https://doi.org/10.1175/1520-0469(1981)038<0572:TQHA>2.0.CO;2, 1981. a
Panosetti, D., Schlemmer, L., and Schär, C.: Bulk convergence behavior
of convection-resolving simulations of summertime deep convection over land,
Clim. Dynam., 55, 215–234, https://doi.org/10.1007/s00382-018-4229-9, 2018. a
Paulat, M., Frei, C., Hagen, M., and Wernli, H.: A gridded dataset of hourly
precipitation in Germany: Its construction, climatology and application,
Meteorol. Z., 17, 719–732, https://doi.org/10.1127/0941-2948/2008/0332,
2008. a
Pearson, K. J., Lister, G. M., Birch, C. E., Allan, R. P., Hogan, R. J., and
Woolnough, S. J.: Modelling the diurnal cycle of tropical convection across
the “grey zone”, Q. J. Roy. Meteor. Soc., 140,
491–499, https://doi.org/10.1002/qj.2145, 2014. a
Prein, A. F., Gobiet, A., Suklitsch, M., Truhetz, H., Awan, N. K., Keuler, K.,
and Georgievski, G.: Added value of convection permitting seasonal
simulations, Clim. Dynam., 41, 2655–2677,
https://doi.org/10.1007/s00382-013-1744-6, 2013. a, b
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S.,
Schmidli, J., Van Lipzig, N. P., and Leung, R.: A review on regional
convection-permitting climate modeling: Demonstrations, prospects, and
challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475,
2015. a
Pudykiewicz, J., Benoit, R., and Staniforth, A.: Preliminary results from a
partial lrtap model based on an existing meteorological forecast model,
Atmos.-Ocean, 23, 267–303, https://doi.org/10.1080/07055900.1985.9649229, 1985. a
Ramsauer, T., Weiß, T., and Marzahn, P.: Comparison of the GPM IMERG final
precipitation product to RADOLAN weather radar data over the topographically
and climatically diverse Germany, Remote Sensing, 10,
https://doi.org/10.3390/rs10122029, 2018. a, b
Raschendorfer, M.: The new turbulence parameterization of LM, COSMO
Newsletter, 1, 89–97,
2001. a
Reinhardt, T. and Seifert, A.: A three-category ice scheme for LMK, COSMO
Newsletter, 6, 115–120, 2006. a
Ricard, D., Lac, C., Riette, S., Legrand, R., and Mary, A.: Kinetic energy
spectra characteristics of two convection-permitting limited-area models
AROME and meso-NH, Q. J. Roy. Meteor. Soc.,
139, 1327–1341, https://doi.org/10.1002/qj.2025, 2013. a, b
Richter, D.: Ergebnisse methodischer Untersuchungen zur Korrektur des
systematischen Meßfehlers des Hellmann-Niederschlagmessers, 194,
Selbstverlag des Deutschen Wetterdienstes, Offenbach am Main, 1995. a
Ritter, B. and Geleyn, J.-F.: A Comprehensive Radiation Scheme for Numerical
Weather Prediction Models with Potential Applications in Climate
Simulations, Mon. Weather Rev., 120, 303–325, https://doi.org/10.1175/1520-0493(1992)120<0303:ACRSFN>2.0.CO;2, 1992. a
Rockel, B., Will, A., and Hense, A.: The regional climate model COSMO-CLM
(CCLM), Meteorol. Z., 17, 347–348,
https://doi.org/10.1127/0941-2948/2008/0309, 2008. a
Romero, R., Doswell, C. A., and Riosalido, R.: Observations and fine-grid
simulations of a convective outbreak in Northeastern Spain: Importance of
diurnal forcing and convective cold pools, Mon. Weather Rev., 129,
2157–2182, https://doi.org/10.1175/1520-0493(2001)129<2157:OAFGSO>2.0.CO;2, 2001. a
Ross, B. B. and Orlanski, I.: The Circulation Associated with a Cold Front.
Part II: Moist Case, J. Atmos. Sci., 35, 445–465,
https://doi.org/10.1175/1520-0469(1978)035<0445:tcawac>2.0.co;2, 1978. a
Schär, C., Fuhrer, O., Arteaga, A., Ban, N., Charpilloz, C., Girolamo,
S. D., Hentgen, L., Hoefler, T., Lapillonne, X., Leutwyler, D., Osterried,
K., Panosetti, D., Rüdisühli, S., Schlemmer, L., Schulthess,
T. C., Sprenger, M., Ubbiali, S., and Wernli, H.: Kilometer-Scale Climate
Models, B. Am. Meteorol. Soc., 101, E567–E587,
https://doi.org/10.1175/BAMS-D-18-0167.1, 2020. a, b
Schlemmer, L., Schär, C., Lüthi, D., and Strebel, L.: A
Groundwater and Runoff Formulation for Weather and Climate Models, J. Adv. Model. Earth Syst., 10, 1809–1832,
https://doi.org/10.1029/2017MS001260, 2018. a, b
Schneider, U., Becker, A., Finger, P., Meyer-Christoffer, A., and Ziese, M.:
GPCC Monitoring Product: Near Real-Time Monthly Land-Surface Precipitation
from Rain-Gauges based on SYNOP and CLIMAT data, Deutscher Wetterdienst,
https://doi.org/10.5676/DWD_GPCC/MP_M_V6_100, 2018. a
Schulthess, T. C., Bauer, P., Wedi, N., Fuhrer, O., Hoefler, T., and
Schär, C.: Reflecting on the Goal and Baseline for Exascale Computing:
A Roadmap Based on Weather and Climate Simulations, Comput. Sci.
Eng., 21, 30–41, https://doi.org/10.1109/MCSE.2018.2888788, 2019. a, b
Schumann, U.: The horizontal spectrum of vertical velocities near the
tropopause from global to gravity wave scales, J. Atmos.
Sci., 76, 3847–3862, https://doi.org/10.1175/JAS-D-19-0160.1, 2019. a
Sevruk, B.: Systematischer Niederschlagsmessfehler in der Schweiz, in: Der
Niederschlag in der Schweiz, no. 31 in Beiträge zur Geologie der
Schweiz-Hydrologie, chap. 3.1, pp. 65–75, Schweizerische Geotechnische
Kommission, Zürich, 1985. a
Sevruk, B.: Rainfall Measurement: Gauges, in: Encyclopedia of Hydrological
Sciences, Part 4. Hydrometeorology, edited by: Anderson, M. G., John Wiley & Sons, Ltd., 35,
8, https://doi.org/10.1002/0470848944.hsa038, 2005. a
Skamarock, W. C.: Evaluating Mesoscale NWP Models Using Kinetic Energy
Spectra, Mon. Weather Rev., 132, 3019–3032, https://doi.org/10.1175/MWR2830.1,
2004. a
Skamarock, W. C. and Klemp, J. B.: A time-split nonhydrostatic atmospheric
model for weather research and forecasting applications, J.
Comput. Phys., 227, 3465–3485, https://doi.org/10.1016/j.jcp.2007.01.037,
2008. a
Smagorinsky, J.: General circulation experiments with the primitive
equations, Mon. Weather Rev., 91, 99–164,
https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2, 1963. a
Smolarkiewicz, P. K. and Pudykiewicz, J. A.: A Class of Semi-Lagrangian
Approximations for Fluids, J. Atmos. Sci., 49, 2082–2096,
https://doi.org/10.1175/1520-0469(1992)049<2082:ACOSLA>2.0.CO;2, 1992. a
Staniforth, A. and Côté, J.: Semi-Lagrangian Integration Schemes
for Atmospheric Models – A Review, Mon. Weather Rev., 119, 2206–2223,
https://doi.org/10.1175/1520-0493(1991)119<2206:SLISFA>2.0.CO;2, 1991. a, b
Stephens, G. L., L'Ecuyer, T., Forbes, R., Gettlemen, A., Golaz, J. C.,
Bodas-Salcedo, A., Suzuki, K., Gabriel, P., and Haynes, J.: Dreary state of
precipitation in global models, J. Geophys. Res.-Atmos.,
115, 1–14, https://doi.org/10.1029/2010JD014532, 2010. a
Sun, Y., Solomon, S., Dai, A., and Portmann, R. W.: How often does it rain?,
J. Climate, 19, 916–934, https://doi.org/10.1175/JCLI3672.1, 2006. a
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in
large-scale models, Mon. Weather Rev., 117, 1779–1800,
https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2, 1989. a, b, c
Ubbiali, S., Schär, C., Schlemmer, L., and Schulthess, T. C.: A
numerical analysis of six physics-dynamics coupling schemes for atmospheric
models, J. Adv. Model. Earth Sy., in review, 2021. a
Vergara-Temprado, J., Ban, N., Panosetti, D., Schlemmer, L., and Schär,
C.: Climate models permit convection at much coarser resolutions than
previously considered, J. Climate, 33, 1915–1933,
https://doi.org/10.1175/JCLI-D-19-0286.1., 2020. a, b
Vergara-Temprado, J., Ban, N., and Schär, C.: Extreme Sub-Hourly
Precipitation Intensities Scale Close to the Clausius-Clapeyron Rate Over
Europe, Geophys. Res. Lett., 48, e2020GL089506,
https://doi.org/10.1029/2020GL089506, 2021. a
Villarini, G. and Krajewski, W. F.: Review of the different sources of
uncertainty in single polarization radar-based estimates of rainfall,
Surv. Geophys., 31, 107–129, https://doi.org/10.1007/s10712-009-9079-x, 2010. a
Wang, S., Liu, J., Wang, J., Qiao, X., and Zhang, J.: Evaluation of GPM IMERG
V05B and TRMM 3B42V7 Precipitation products over high mountainous tributaries
in Lhasa with dense rain gauges, Remote Sensing, 11,
https://doi.org/10.3390/rs11182080, 2019. a, b
Wedi, N., Yessad, K., and Untch, A.: The non-hydrostatic global IFS/ARPEGE
model: model formulation and testing, ECMWF Technical Memoranda, p. 34,
https://doi.org/10.21957/tl4f0ao4t, 2009. a
Wedi, N. P.: Increasing horizontal resolution in numerical weather prediction
and climate simulations: Illusion or panacea?, Philos. T. Roy. Soc. A, 372, 20130289,
https://doi.org/10.1098/rsta.2013.0289, 2014. a
Wedi, N. P., Hamrud, M., and Mozdzynski, G.: A fast spherical harmonics
transform for global NWP and climate models, Mon. Weather Rev., 141,
3450–3461, https://doi.org/10.1175/MWR-D-13-00016.1, 2013. a
Wedi, N. P., Dueben, P., Anantharaj, V. G., Bauer, P., Boussetta, S., Browne,
P., Deconinck, W., Gaudin, W., Hadade, I., Hatfield, S., Iffrig, O., Lopez,
P., Maciel, P., Mueller, A., Polichtchouk, I., Saarinen, S., Quintino, T.,
and Vitart, F.: A baseline for global weather and climate simulations at 1 km resolution, J.
Adv. Model. Earth Sy., 12, e2020MS002192,
https://doi.org/10.1029/2020MS002192, 2020. a, b
Weisman, M. L., Skamarock, W. C., and Klemp, J. B.: The Resolution Dependence
of Explicitly Modeled Convective Systems, Mon. Weather Rev., 125,
527–548, https://doi.org/10.1175/1520-0493(1997)125<0527:TRDOEM>2.0.CO;2, 1997.
a, b
Wicker, L. J. and Skamarock, W. C.: Time-Splitting Methods for Elastic Models
Using Forward Time Schemes, Mon. Weather Rev., 130, 2088–2097,
https://doi.org/10.1175/1520-0493(2002)130<2088:TSMFEM>2.0.CO;2, 2002. a
Williamson, D. L. and Olson, J. G.: Dependence of aqua-planet simulations on
time step, Q. J. Roy. Meteor. Soc., 129,
2049–2064, https://doi.org/10.1256/qj.02.62, 2003. a
Winterrath, T., Brendel, C., Hafer, M., Junghänel, T., Klameth, A.,
Walawender, E., Weigl, E., and Becker, A.: Erstellung einer
radargestützten Niederschlagsklimatologie, 251, Deutscher
Wetterdienst, https://doi.org/10.17169/refubium-25153, 2017. a
Wüest, M., Frei, C., Altenhoff, A., Hagen, M., Litschi, M., and
Schär, C.: A gridded hourly precipitation dataset for Switzerland
using rain-gauge analysis and radar-based disaggregation, Int.
J. Climatol., 30, 1764–1775, https://doi.org/10.1002/joc.2025, 2010. a
Yang, G. Y. and Slingo, J.: The diurnal cycle in the tropics, Mon. Weather
Rev., 129, 784–801, https://doi.org/10.1175/1520-0493(2001)129<0784:TDCITT>2.0.CO;2,
2001. a
Zeman, C., Wedi, N. P., Dueben, P. D., Ban, N., and Schär, C.: Model intercomparison of COSMO 5.0 and IFS 45r1 at kilometer-scale grid spacing (Version 1.0) [data set], Zenodo, https://doi.org/10.5281/zenodo.4479130, 2021. a
Short summary
Kilometer-scale atmospheric models allow us to partially resolve thunderstorms and thus improve their representation. We present an intercomparison between two distinct atmospheric models for 2 summer days with heavy thunderstorms over Europe. We show the dependence of precipitation and vertical wind speed on spatial and temporal resolution and also discuss the possible influence of the system of equations, numerical methods, and diffusion in the models.
Kilometer-scale atmospheric models allow us to partially resolve thunderstorms and thus improve...