Articles | Volume 9, issue 2
https://doi.org/10.5194/gmd-9-567-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-567-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
10 Feb 2016
Model description paper |
| 10 Feb 2016
LIMA (v1.0): A quasi two-moment microphysical scheme driven by a multimodal population of cloud condensation and ice freezing nuclei
CNRM-GAME, Météo-France & CNRS, 42 avenue Gaspard Coriolis, 31057 Toulouse, France
J.-P. Pinty
Laboratoire d'Aérologie, University of Toulouse/CNRS, 14 avenue Edouard Belin, 31400 Toulouse, France
S. Berthet
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales, CNRS/IRD/University of Toulouse/CNES, 14 avenue Edouard Belin, 31400 Toulouse, France
M. Leriche
Laboratoire d'Aérologie, University of Toulouse/CNRS, 14 avenue Edouard Belin, 31400 Toulouse, France
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Cloé David, Clotilde Augros, Benoît Vié, François Bouttier, and Tony Le Bastard
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Simulations of storm characteristics and associated radar signatures were improved, especially under the freezing level, using an advanced cloud scheme. Discrepancies between observations and forecasts at and above the melting layer highlighted issues in both the radar forward operator and the microphysics. To overcome part of these issues, different parametrizations of the operator were suggested. This work aligns with the future integration of polarimetric data into assimilation systems.
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
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Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
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This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
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Simulations of storm characteristics and associated radar signatures were improved, especially under the freezing level, using an advanced cloud scheme. Discrepancies between observations and forecasts at and above the melting layer highlighted issues in both the radar forward operator and the microphysics. To overcome part of these issues, different parametrizations of the operator were suggested. This work aligns with the future integration of polarimetric data into assimilation systems.
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
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Setigui Aboubacar Keita, Eric Girard, Jean-Christophe Raut, Maud Leriche, Jean-Pierre Blanchet, Jacques Pelon, Tatsuo Onishi, and Ana Cirisan
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Émilie Poirier, Julie M. Thériault, and Maud Leriche
Hydrol. Earth Syst. Sci., 23, 4097–4111, https://doi.org/10.5194/hess-23-4097-2019, https://doi.org/10.5194/hess-23-4097-2019, 2019
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The impact of phase changes aloft on the precipitation distribution in the Kananaskis Valley, Alberta, was studied. The model reproduces well the atmospheric conditions and precipitation pattern. In this region, sublimation has a greater impact on the evolution of the precipitation than melting. The trajectories of hydrometeors explain the precipitation distribution in the valley, which can impact snowpacks. The amount of snow at the surface also depends on the strength of the downslope flow.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
Short summary
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This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Fabien Brosse, Maud Leriche, Céline Mari, and Fleur Couvreux
Atmos. Chem. Phys., 18, 6601–6624, https://doi.org/10.5194/acp-18-6601-2018, https://doi.org/10.5194/acp-18-6601-2018, 2018
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The cleansing capacity of the atmosphere is studied through the hydroxyl radical (OH) chemical reactivity in numerical simulations of natural and urban environments. Turbulence-driven segregation of chemical compounds in the atmospheric boundary layer is explored and may partially explain discrepancies between observed and modeled OH reactivity in both environments.
Clémence Rose, Nadine Chaumerliac, Laurent Deguillaume, Hélène Perroux, Camille Mouchel-Vallon, Maud Leriche, Luc Patryl, and Patrick Armand
Atmos. Chem. Phys., 18, 2225–2242, https://doi.org/10.5194/acp-18-2225-2018, https://doi.org/10.5194/acp-18-2225-2018, 2018
Short summary
Short summary
A detailed aqueous phase mechanism CLEPS 1.1 is coupled with warm microphysics including activation of aerosol particles into cloud droplets. Simulated aqueous concentrations of carboxylic acids are close to the long-term measurements conducted at Puy de Dôme (France). Sensitivity tests show that formic and acetic acids mainly originate from the gas phase with highly variable aqueous-phase reactivity depending on cloud pH, while C3–C4 carboxylic acids mainly originate from the particulate phase.
Camille Mouchel-Vallon, Laurent Deguillaume, Anne Monod, Hélène Perroux, Clémence Rose, Giovanni Ghigo, Yoann Long, Maud Leriche, Bernard Aumont, Luc Patryl, Patrick Armand, and Nadine Chaumerliac
Geosci. Model Dev., 10, 1339–1362, https://doi.org/10.5194/gmd-10-1339-2017, https://doi.org/10.5194/gmd-10-1339-2017, 2017
Short summary
Short summary
The Cloud Explicit Physico-chemical Scheme (CLEPS 1.0) describes oxidation of water-soluble organic compounds resulting from isoprene oxidation. It is based on structure activity relationships (SARs) (global rate constants and branching ratios for HO• abstraction and addition) and GROMHE SAR (Henry's law constants for undocumented species). It is coupled to the MCM gas phase mechanism and is included in a model using the DSMACC model and KPP to analyze experimental and field data.
Alicia Gressent, Bastien Sauvage, Daniel Cariolle, Mathew Evans, Maud Leriche, Céline Mari, and Valérie Thouret
Atmos. Chem. Phys., 16, 5867–5889, https://doi.org/10.5194/acp-16-5867-2016, https://doi.org/10.5194/acp-16-5867-2016, 2016
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In chemical transport models, NOx emitted by lightning (LNOx) is instantaneously diluted into the grid. A plume-in-grid parameterization to account for the sub-grid chemistry of LNOx is presented. This approach was implemented into the GEOS-Chem model and leads to a relative increase of NOx and O3 (18 % and 2 %, respectively, in July) on a large scale downwind of lightning emissions and a relative decrease (25 % and 8 %, respectively, over central Africa in July) over the regions of emissions.
C. Barbet, L. Deguillaume, N. Chaumerliac, M. Leriche, A. Berger, E. Freney, A. Colomb, K. Sellegri, L. Patryl, and P. Armand
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-13395-2015, https://doi.org/10.5194/acpd-15-13395-2015, 2015
Preprint withdrawn
M. Leriche, J.-P. Pinty, C. Mari, and D. Gazen
Geosci. Model Dev., 6, 1275–1298, https://doi.org/10.5194/gmd-6-1275-2013, https://doi.org/10.5194/gmd-6-1275-2013, 2013
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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.
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.
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.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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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, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS 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 e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
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. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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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-km 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 improved representation of clouds and visibility.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
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Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has 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 have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-194, https://doi.org/10.5194/gmd-2024-194, 2024
Revised manuscript accepted for GMD
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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.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Cited articles
ACPC: Aerosols, Clouds, Precipitation and Climate, Steering Committee:
Science Plan and Implementation Strategy, Tech. rep., IGAC (International
Global Atmospheric Chemistry), Boulder, available at:
http://www.igacproject.org/sites/all/themes/bluemasters/images/2009_ACPC_SciencePlan_FINAL.pdf
(last access: 2 September 2015), 2009.
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness,
Science, 245, 1227–1230, 1989.
Andreae, M. O., Rosenfeld, D., Artaxo, P., Costa, A., Frank, G., Longo, K.,
and Silva-Dias, M.: Smoking rain clouds over the Amazon, Science, 303,
1337–1342, 2004.
Aouizerats, B., Thouron, O., Tulet, P., Mallet, M., Gomes, L., and Henzing,
J. S.: Development of an online radiative module for the computation of
aerosol optical properties in 3-D atmospheric models: validation during the
EUCAARI campaign, Geosci. Model Dev., 3, 553–564,
https://doi.org/10.5194/gmd-3-553-2010, 2010.
Barahona, D. and Nenes, A.: Parameterizing the competition between
homogeneous and heterogeneous freezing in ice cloud formation – polydisperse
ice nuclei, Atmos. Chem. Phys., 9, 5933–5948, https://doi.org/10.5194/acp-9-5933-2009,
2009.
Beheng, K. D.: Microphysical properties of glaciating cumulus clouds:
comparison of measurements with a numerical simulation, Q. J. Roy. Meteor.
Soc., 113, 1377–1382,
https://doi.org/10.1002/qj.49711347815,
1987.
Berry, E. X. and Reinhardt, R. L.: An analysis of cloud drop growth by
collection Part II. Single initial distributions, J. Atmos. Sci., 31,
1825–1831, 1974.
Berthet, S., Leriche, M., Pinty, J.-P., Cuesta, J., and Pigeon, G.:
Scavenging of aerosol particles by rain in a cloud resolving model, Atmos.
Res., 96, 325–336, 2010.
Caniaux, G., Redelsperger, J., and Lafore, J.: A numerical study of the
stratiform region of a fast-moving squall line. Part I: General description
and water and heat budgets, J. Atmos. Sci., 51, 2046–2074, 1994.
Chou, C., Formenti, P., Maille, M., Ausset, P., Helas, G., Harrison, M., and
Osborne, S.: Size distribution, shape, and composition of mineral dust
aerosols collected during the African Monsoon Multidisciplinary Analysis
Special Observation Period 0: dust and biomass-burning experiment field
campaign in Niger, January 2006, J. Geophys. Res.-Atmos.,
113, D00C10,
https://doi.org/10.1029/2008JD009897, 2008.
Cohard, J.-M. and Pinty, J.-P.: A comprehensive two-moment warm microphysical
bulk scheme. I: Description and tests, Q. J. Roy. Meteor. Soc., 126,
1815–1842,
https://doi.org/10.1002/qj.49712656613,
2000a.
Cohard, J.-M. and Pinty, J.-P.: A comprehensive two-moment warm microphysical
bulk scheme. II: 2D experiments with a non-hydrostatic model, Q. J. Roy.
Meteor. Soc., 126, 1843–1859,
https://doi.org/10.1002/qj.49712656614,
2000b.
Cohard, J.-M., Pinty, J.-P., and Bedos, C.: Extending Twomey's analytical
estimate of nucleated cloud droplet concentrations from CCN spectra, J.
Atmos. Sci., 55, 3348–3357, 1998.
Cohard, J.-M., Pinty, J.-P., and Suhre, K.: On the parameterization of
activation spectra from cloud condensation nuclei microphysical properties,
J. Geophys. Res.-Atmos., 105, 11753–11766,
https://doi.org/10.1029/1999JD901195,
2000.
DeMott, P., Prenni, A., Liu, X., Kreidenweis, S., Petters, M., Twohy, C.,
Richardson, M., Eidhammer, T., and Rogers, D.: Predicting global atmospheric
ice nuclei distributions and their impacts on climate, P. Natl. Acad. Sci.
USA, 107, 11217–11222, 2010.
Diehl, K. and Wurzler, S.: Heterogeneous drop freezing in the immersion mode:
model calculations considering soluble and insoluble particles in the drops,
J. Atmos. Sci., 61, 2063–2072, 2004.
Ferek, R. J., Garrett, T., Hobbs, P. V., Strader, S., Johnson, D.,
Taylor, J. P., Nielsen, K., Ackerman, A. S., Kogan, Y., Liu, Q.,
Albrecht, B. A., and Babb, D.: Drizzle suppression in ship tracks, J. Atmos.
Sci., 57, 2707–2728, 2000.
Fouquart, Y. and Bonnel, B.: Computations of solar heating of the earth's
atmosphere – a new parameterization, Beitraege zur Physik der Atmosphaere,
53, 35–62, 1980.
Geoffroy, O., Brenguier, J.-L., and Sandu, I.: Relationship between drizzle
rate, liquid water path and droplet concentration at the scale of a
stratocumulus cloud system, Atmos. Chem. Phys., 8, 4641–4654,
https://doi.org/10.5194/acp-8-4641-2008, 2008.
Gilmore, M. S. and Straka, J. M.: The Berry and Reinhardt autoconversion
parameterization: a digest, J. Appl. Meteorol. Clim., 47, 375–396, 2008.
Hallett, J. and Mossop, S. C.: Production of secondary ice particles during
the riming process, Nature, 249, 26–28,
https://doi.org/10.1038/249026a0, 1974.
Harrington, J. Y., Meyers, M. P., Walko, R. L., and Cotton, W. R.:
Parameterization of ice crystal conversion processes due to vapor deposition
for mesoscale models using double-moment basis functions. Part I: Basic
formulation and parcel model results, J. Atmos. Sci., 52, 4344–4366,
https://doi.org/10.1175/1520-0469(1995)052<4344:POICCP>2.0.CO;2,
1995.
Johnson, B., Shine, K., and Forster, P.: The semi-direct aerosol effect:
impact of absorbing aerosols on marine stratocumulus, Q. J. Roy. Meteor.
Soc., 130, 1407–1422, 2004.
Kärcher, B. and Lohmann, U.: A parameterization of cirrus cloud
formation: homogeneous freezing of supercooled aerosols, J. Geophys.
Res.-Atmos.,
107, AAC4.1–AAC4.10,
https://doi.org/10.1029/2001JD000470, 2002.
Khairoutdinov, M. and Kogan, Y.: A new cloud physics parameterization in a
large-eddy simulation model of marine stratocumulus, Mon. Weather Rev., 128,
229–243, 2000.
Khvorostyanov, V. I. and Curry, J. A.: The theory of ice nucleation by
heterogeneous freezing of deliquescent mixed CC N. Part I: Critical radius,
energy, and nucleation rate, J. Atmos. Sci., 61, 2676–2691, 2004.
Kogan, Y.: A cumulus cloud microphysics parameterization for cloud-resolving
models, J. Atmos. Sci., 70, 1423–1436, 2013.
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.
Lascaux, F., Richard, E., and Pinty, J.-P.: Numerical simulations of three
different MAP IOPs and the associated microphysical processes, Q. J. Roy.
Meteor. Soc., 132, 1907–1926, 2006.
Lebo, Z. J. and Morrison, H.: A novel Scheme for parameterizing aerosol
processing in warm clouds, J. Atmos. Sci., 70, 3576–3598, 2013.
Lim, K.-S. S. and Hong, S.-Y.: Development of an effective double-moment
cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for
weather and climate models, Mon. Weather Rev., 138, 1587–1612, 2010.
Long, A. B.: Solutions to the droplet collection equation for polynomial
kernels, J. Atmos. Sci., 31, 1040–1052, 1974.
Meyers, M. P., DeMott, P. J., and Cotton, W. R.: New primary ice-nucleation
parameterizations in an explicit cloud model, J. Appl. Meteorol., 31,
708–721, 1992.
Meyers, M. P., Walko, R. L., Harrington, J. Y., and Cotton, W. R.: New RAMS
cloud microphysics parameterization. Part II: The two-moment scheme, Atmos.
Res., 45, 3–39, 1997.
Milbrandt, J. and Yau, M.: A multimoment bulk microphysics parameterization.
Part I: Analysis of the role of the spectral shape parameter, J. Atmos. Sci.,
62, 3051–3064, 2005a.
Milbrandt, J. and Yau, M.: A multimoment bulk microphysics parameterization.
Part II: A proposed three-moment closure and scheme description, J. Atmos.
Sci., 62, 3065–3081, 2005b.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and
Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a
validated correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102,
16663–16682, 1997.
Morrison, H. and Grabowski, W. W.: Comparison of bulk and bin warm-rain
microphysics models using a kinematic framework, J. Atmos. Sci., 64,
2839–2861, 2007.
Morrison, H. and Grabowski, W. W.: A novel approach for representing ice
microphysics in models: description and tests using a kinematic framework, J.
Atmos. Sci., 65, 1528–1548, 2008.
Morrison, H., Curry, J., and Khvorostyanov, V.: A new double-moment
microphysics parameterization for application in cloud and climate models.
Part I: Description, J. Atmos. Sci., 62, 1665–1677, 2005.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics
on the development of trailing stratiform precipitation in a simulated squall
line: comparison of one-and two-moment schemes, Mon. Weather Rev., 137,
991–1007, 2009.
Muhlbauer, A. and Lohmann, U.: Orographic mixed-phase stratiform cloud case,
in: WMO Cloud Modeling Workshop, Cozumel, Mexico, 14–17 July 2008, available
at:
http://www.rap.ucar.edu/~gthompsn/workshop2008/case1_description.pdf
(last access: 2 September 2015), 1–22, 2008.
Muhlbauer, A., Grabowski, W. W., Malinowski, S. P., Ackerman, T. P., Bryan,
G. H., Lebo, Z. J., Milbrandt, J. A., Morrison, H., Ovchinnikov, M.,
Tessendorf, S., Thériault, J. M., and Thompson, G.: Reexamination of the
state of the art of cloud modeling shows real improvements, B. Am. Meteorol.
Soc., 94, ES45–ES48, 2013.
Niedermeier, D., Shaw, R. A., Hartmann, S., Wex, H., Clauss, T.,
Voigtländer, J., and Stratmann, F.: Heterogeneous ice nucleation:
exploring the transition from stochastic to singular freezing behavior,
Atmos. Chem. Phys., 11, 8767–8775, https://doi.org/10.5194/acp-11-8767-2011, 2011.
Phillips, V. T., DeMott, P. J., and Andronache, C.: An empirical
parameterization of heterogeneous ice nucleation for multiple chemical
species of aerosol, J. Atmos. Sci., 65, 2757–2783, 2008.
Phillips, V. T., Demott, P. J., Andronache, C., Pratt, K. A., Prather, K. A.,
Subramanian, R., and Twohy, C.: Improvements to an empirical parameterization
of heterogeneous ice nucleation and its comparison with observations, J.
Atmos. Sci., 70, 378–409, 2013.
Pinty, J. and Jabouille, P.: A mixed-phase cloud parameterization for use in
a mesoscale non-hydrostatic model: simulations of a squall line and of
orographic precipitations, in: Conf. on Cloud Physics, 17–21 August 1998,
Everett, Washington, 217–220, 1998.
Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P.:
Numerical Recipes in FORTRAN: The Art of Scientific Computing, Cambridge
Univ. Press, New York, 963 pp., 1992.
Pruppacher, H. R.: A new look at homogeneous ice nucleation in supercooled
water drops, J. Atmos. Sci., 52, 1924–1933,
https://doi.org/10.1175/1520-0469(1995)052<1924:ANLAHI>2.0.CO;2,
1995.
Pruppacher, H. R. and Klett, J. D.: Microphysics of Clouds and Precipitation,
Kluwer Academic Publishers, Dordrecht and Boston, 1997.
Reisin, T., Levin, Z., and Tzivion, S.: Rain production in convective clouds
as simulated in an axisymmetric model with detailed microphysics. Part I:
Description of the model, J. Atmos. Sci., 53, 497–519, 1996.
Rosenfeld, D., Lohmann, U., Raga, G. B., O'Dowd, C. D., Kulmala, M.,
Fuzzi, S., Reissell, A., and Andreae, M. O.: Flood or drought: how do
aerosols affect precipitation?, Science, 321, 1309–1313, 2008.
Saleeby, S. M. and van den Heever, S. C.: Developments in the CSU-RAMS
aerosol model: emissions, nucleation, regeneration, deposition, and
radiation, J. Appl. Meteorol. Clim., 52, 2601–2622, 2013.
Schär, C., Leuenberger, D., Fuhrer, O., Lüthi, D., and Girard, C.: A
new terrain-following vertical coordinate formulation for atmospheric
prediction models, Mon. Weather Rev., 130, 2459–2480, 2002.
Seifert, A. and Beheng, K.: A two-moment cloud microphysics parameterization
for mixed-phase clouds. Part 1: Model description, Meteorol. Atmos. Phys.,
92, 45–66, 2006.
Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P.,
Bouttier, F., Lac, C., and Masson, V.: The AROME-France convective-scale
operational model, Mon. Weather Rev., 139, 976–991, 2011.
Slinn, W.: Precipitation scavenging, in: Atmospheric Sciences and Power
Production – 1979, Division of biomedical environment research, US
department of energy, Washington D.C., chapter 11, 1983.
Storer, R. L., van den Heever, S. C., and L'Ecuyer, T. S.: Observations of
aerosol-induced convective invigoration in the tropical east Atlantic, J.
Geophys. Res.-Atmos., 119, 3963–3975,
https://doi.org/10.1002/2013jd020272,
2014.
Tao, W.-K., Chen, J.-P., Li, Z., Wang, C., and Zhang, C.: Impact of aerosols
on convective clouds and precipitation, Rev. Geophys., 50, RG2001,
https://doi.org/10.1029/2011RG000369, 2012.
Thompson, G. and Eidhammer, T.: A study of aerosol impacts on clouds and
precipitation development in a large winter cyclone, J. Atmos. Sci., 71,
3636–3658, 2014.
Thompson, G., Field, P. R., Rasmussen, R. M., and Hall, W. D.: Explicit
forecasts of winter precipitation using an improved bulk microphysics scheme.
Part II: Implementation of a new snow parameterization, Mon. Weather Rev.,
136, 5095–5115, 2008.
Tripoli, G. J., Flatau, P. J., and Cotton, W. R.: Generalized microphysics
scheme for use in mesoscale/cloud models, in: reprints from the 10th
International Cloud Physics Conference, 15–20 August 1988, Bad Homburg,
Germany, Vol. 1, 109–111, available at:
http://adsabs.harvard.edu/abs/1988clph.conf..109T (last access: 2
September 2015), 1988.
Tulet, P., Crassier, V., Cousin, F., Suhre, K., and Rosset, R.: ORILAM, a
three-moment lognormal aerosol scheme for mesoscale atmospheric model: online
coupling into the Meso-NH-C model and validation on the Escompte campaign, J.
Geophys. Res.-Atmos., 110, D18201, https://doi.org/10.1029/2004JD005716, 2005.
Twomey, S.: The nuclei of natural cloud formation part II: The
supersaturation in natural clouds and the variation of cloud droplet
concentration, Geofisica pura e applicata, 43, 243–249, 1959.
Twomey, S.: The influence of pollution on the shortwave albedo of clouds, J.
Atmos. Sci., 34, 1149–1152, 1977.
Tzivion, S., Feingold, G., and Levin, Z.: The evolution of raindrop spectra.
Part II: Collisional collection/breakup and evaporation in a rainshaft, J.
Atmos. Sci., 46, 3312–3328, 1989.
Vié, B. and Pinty, J.-P.: LIMA: a two-moment mixed-phase microphysical
scheme driven by a multimodal population of cloud condensation nuclei and ice
freezing nuclei, in: 14th AMS conference on cloud physics, 7–11 July, poster
number 27, Boston, 2014.
Wall, C., Zipser, E., and Liu, C.: An investigation of the aerosol indirect
effect on convective intensity using satellite observations, J. Atmos. Sci.,
71, 430–447, 2014.
Short summary
LIMA, a new quasi two-moment, mixed-phase microphysical scheme, is introduced. LIMA relies on the prognostic evolution of a multimodal aerosol population and the careful description of their nucleating properties that enable cloud droplets and pristine ice to form. This paper describes LIMA and illustrates its ability to represent aerosol-cloud interactions for 2-D idealized simulations of a squall line and orographic cold clouds.
LIMA, a new quasi two-moment, mixed-phase microphysical scheme, is introduced. LIMA relies on...
