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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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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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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Christian Zeman and Christoph Schär
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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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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
Related subject area
Atmospheric sciences
Low-level jets in the North and Baltic seas: mesoscale model sensitivity and climatology using WRF V4.2.1
SynRad v1.0: a radar forward operator to simulate synthetic weather radar observations from volcanic ash clouds
Chempath 1.0: an open-source pathway analysis program for photochemical models
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Atmospheric moisture tracking with WAM2layers v3
A new set of indicators for model evaluation complementing FAIRMODE's modelling quality objective (MQO)
Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Development of a High-Resolution Coupled SHiELD-MOM6 Model. Part I – Model Overview, Coupling Technique, and Validation in a Regional Setup
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
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Low-level jets (LLJs) are strong winds in the lower atmosphere that are important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025, https://doi.org/10.5194/gmd-18-4417-2025, 2025
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A numerical model that simulates the measurement processes behind the ground-based radars used to detect volcanic ash clouds is introduced. Using weather radars to detect volcanic clouds is not ideal, as fine ash particles are smaller than raindrops and remain undetected. We evaluate the performance of weather radars to study ash clouds and to identify optimal frequencies that balance the trade-off between a higher return signal and the higher path attenuation that comes at these higher frequencies.
Daniel Garduno Ruiz, Colin Goldblatt, and Anne-Sofie Ahm
Geosci. Model Dev., 18, 4433–4454, https://doi.org/10.5194/gmd-18-4433-2025, https://doi.org/10.5194/gmd-18-4433-2025, 2025
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Photochemical models describe how the composition of the atmosphere changes due to chemical reactions, transport, and other processes. These models are useful for studying the composition of the Earth's and other planets' atmospheres. Understanding the results of these models can be difficult. Here, we build on previous work to develop open-source code that can identify the reaction chains (pathways) that produce the results of these models, facilitating the understanding of these results.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
Geosci. Model Dev., 18, 4353–4398, https://doi.org/10.5194/gmd-18-4353-2025, https://doi.org/10.5194/gmd-18-4353-2025, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line And Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, this model is valuable for airglow research and astronomical observatories.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
Geosci. Model Dev., 18, 4335–4352, https://doi.org/10.5194/gmd-18-4335-2025, https://doi.org/10.5194/gmd-18-4335-2025, 2025
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We introduce a new version of WAM2layers (Water Accounting Model – 2 layers), a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data had become a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent, reliable, and easier to maintain.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
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We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and winter–summer gradients reveal issues. O3 evaluation shows that seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1690, https://doi.org/10.5194/egusphere-2025-1690, 2025
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We introduce a new high-resolution model that couple the atmosphere and ocean to better simulate extreme weather events. It combines GFDL’s advanced atmospheric and ocean models with a powerful coupling system that allows robust and efficient two-way interactions. Simulations show the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model is a key step toward improving extreme weather forecast.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
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...