Articles | Volume 9, issue 2
https://doi.org/10.5194/gmd-9-697-2016
© 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-9-697-2016
© 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
| 
18 Feb 2016
Model description paper |
| 18 Feb 2016
ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes
Scuola Normale Superiore, Pisa, Italy
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Pisa, Italy
Dipartimento di Matematica, Università degli Studi di Pisa, Pisa, Italy
T. Esposti Ongaro
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Pisa, Italy
L. C. Berselli
Dipartimento di Matematica, Università degli Studi di Pisa, Pisa, Italy
Related authors
Emmie M. Bonilauri, Catherine Aaron, Matteo Cerminara, Raphaël Paris, Tomaso Esposti Ongaro, Benedetta Calusi, Domenico Mangione, and Andrew J. L. Harris
EGUsphere, https://doi.org/10.5194/egusphere-2024-221, https://doi.org/10.5194/egusphere-2024-221, 2024
Short summary
Short summary
Currently at Stromboli, for a locally generated tsunami, only 4 minutes of warning are available. We combined tsunami simulations and human exposure to complete a risk analysis. We linked the predicted inundation area and the tsunami warning signals to assess the hazard posed by future tsunamis, and to design escape routes to reach safe areas and to optimise evacuation times. Such products can be used by Civil Protection agencies on Stromboli Island.
Sara Lenzi, Matteo Cerminara, Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, and Antonello Provenzale
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-28, https://doi.org/10.5194/gmd-2020-28, 2020
Revised manuscript not accepted
Emmie M. Bonilauri, Catherine Aaron, Matteo Cerminara, Raphaël Paris, Tomaso Esposti Ongaro, Benedetta Calusi, Domenico Mangione, and Andrew J. L. Harris
EGUsphere, https://doi.org/10.5194/egusphere-2024-221, https://doi.org/10.5194/egusphere-2024-221, 2024
Short summary
Short summary
Currently at Stromboli, for a locally generated tsunami, only 4 minutes of warning are available. We combined tsunami simulations and human exposure to complete a risk analysis. We linked the predicted inundation area and the tsunami warning signals to assess the hazard posed by future tsunamis, and to design escape routes to reach safe areas and to optimise evacuation times. Such products can be used by Civil Protection agencies on Stromboli Island.
Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, and Samantha Engwell
Geosci. Model Dev., 16, 6309–6336, https://doi.org/10.5194/gmd-16-6309-2023, https://doi.org/10.5194/gmd-16-6309-2023, 2023
Short summary
Short summary
We present version 2 of the numerical code IMEX-SfloW2D. With this version it is possible to simulate a wide range of volcanic mass flows (pyroclastic avalanches, lahars, pyroclastic surges), and here we present its application to transient dilute pyroclastic density currents (PDCs). A simulation of the 1883 Krakatau eruption demonstrates the capability of the numerical model to face a complex natural case involving the propagation of PDCs over the sea surface and across topographic obstacles.
Alessandro Tadini, Andrea Bevilacqua, Augusto Neri, Raffaello Cioni, Giovanni Biagioli, Mattia de'Michieli Vitturi, and Tomaso Esposti Ongaro
Solid Earth, 12, 119–139, https://doi.org/10.5194/se-12-119-2021, https://doi.org/10.5194/se-12-119-2021, 2021
Short summary
Short summary
In this paper we test a simplified numerical model for pyroclastic density currents or PDCs (mixtures of hot gas, lapilli and ash moving across the landscape under the effect of gravity). The aim is quantifying the differences between real and modelled deposits of some PDCs of the 79 CE eruption of Vesuvius, Italy. This step is important because in the paper it is demonstrated that this simplified model is useful for constraining input parameters for more computationally expensive models.
Sara Lenzi, Matteo Cerminara, Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, and Antonello Provenzale
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-28, https://doi.org/10.5194/gmd-2020-28, 2020
Revised manuscript not accepted
Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, Giacomo Lari, and Alvaro Aravena
Geosci. Model Dev., 12, 581–595, https://doi.org/10.5194/gmd-12-581-2019, https://doi.org/10.5194/gmd-12-581-2019, 2019
Short summary
Short summary
Pyroclastic avalanches are a type of granular flow generated at active volcanoes by different mechanisms, including the collapse of steep pyroclastic deposits (e.g., scoria and ash cones) and fountaining during moderately explosive eruptions. We present IMEX_SfloW2D, a depth-averaged flow model describing the granular mixture as a single-phase granular fluid. Benchmark cases and preliminary application to the simulation of the 11 February pyroclastic avalanche at Mt. Etna (Italy) are shown.
S. Carcano, L. Bonaventura, T. Esposti Ongaro, and A. Neri
Geosci. Model Dev., 6, 1905–1924, https://doi.org/10.5194/gmd-6-1905-2013, https://doi.org/10.5194/gmd-6-1905-2013, 2013
Related subject area
Atmospheric sciences
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
RoadSurf 1.1: open-source road weather model library
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
A general comprehensive evaluation method for cross-scale precipitation forecasts
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands
Balloon drift estimation and improved position estimates for radiosondes
Emission ensemble approach to improve the development of multi-scale emission inventories
What is the relative impact of nudging and online coupling on meteorological variables, pollutant concentrations and aerosol optical properties?
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
Short summary
Short summary
Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
Short summary
Short summary
Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
Short summary
Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
Short summary
Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary
Short summary
Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
Short summary
Short summary
RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
Short summary
Short summary
The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
Short summary
Short summary
We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
Short summary
Short summary
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
Short summary
Short summary
By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
Short summary
Short summary
We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
Short summary
Short summary
This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
Short summary
Short summary
Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
Short summary
Short summary
The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
Short summary
Short summary
The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
Short summary
Short summary
There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
Short summary
Short summary
This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
Short summary
Short summary
This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
Short summary
Short summary
We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
Short summary
Short summary
This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
Short summary
Short summary
Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
Short summary
Short summary
In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
Short summary
Short summary
We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
Short summary
Short summary
For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
Short summary
Short summary
Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
Short summary
Short summary
This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
Short summary
Short summary
This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
Short summary
Short summary
An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
Short summary
Short summary
This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
Short summary
Short summary
Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Short summary
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary
Short summary
This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
Short summary
Short summary
Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
Short summary
Short summary
Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
Short summary
Short summary
Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Short summary
Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Short summary
An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
Short summary
Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Short summary
In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary
Short summary
A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
Short summary
Short summary
The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
Short summary
Short summary
In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
Short summary
Short summary
The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
EGUsphere, https://doi.org/10.22541/essoar.169903618.82717612/v2, https://doi.org/10.22541/essoar.169903618.82717612/v2, 2024
Short summary
Short summary
Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate of the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
Short summary
Short summary
In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
Short summary
Short summary
Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
Short summary
Short summary
This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Cited articles
Bagheri, G., Bonadonna, C., Manzella, I.,
Pontelandolfo, P., and Haas, P.: Dedicated vertical wind tunnel for the
study of sedimentation of non-spherical particles., Rev. Sci. Instrum., 84,
054501, https://doi.org/10.1063/1.4805019,
2013.
Balachandar, S.: A scaling analysis for point-particle approaches to
turbulent multiphase flows, Int. J. Multiph. Flow, 35, 801–810,
https://doi.org/10.1016/j.ijmultiphaseflow.2009.02.013,
2009.
Balachandar, S. and Eaton, J. K.: Turbulent dispersed multiphase flow, Ann.
Rev. Fluid Mech., 42, 111–133,
https://doi.org/10.1146/annurev.fluid.010908.165243,
2010.
Bardina, J., Ferziger, J. H., and Reynolds, W. C.: Improved Subgrid Scale
Models for Large Eddy Simulation, 1980, American Institute of Aeronautics
and Astronautics, 13th Fluid and Plasma Dynamics Conference, Snowmass, Pap.
No. 80, Colo., 14–16 July, 1980.
Bernardini, M. and Pirozzoli, S.: A general strategy for the optimization of
Runge–Kutta schemes for wave propagation phenomena, J. Comput. Phys., 228,
4182–4199, 2009.
Berselli, L., Iliescu, T., and Layton, W. J.: Mathematics of Large Eddy
Simulation of Turbulent Flows, Springer Science & Business Media,
Springer-Verlag Berlin Heidelberg, Germany, 356 pp., 2005.
Berselli, L. C., Cerminara, M., and Iliescu, T.: Disperse two-phase flows,
with applications to geophysical problems, Pure Appl. Geophys., 172,
181–196,
https://doi.org/10.1007/s00024-014-0889-5,
2015.
Blaisdell, G. A., Mansour, N. N., and Reynolds, W. C.: Numerical Simulation
of Compressible Homogeneous Turbulence, Stanford University, Dept. of Mech.
Eng., Thermosciences Div. Rep. TF-50, 1991.
Boffetta, G., Celani, A., Lillo, F. D., and Musacchio, S.: The Eulerian
description of dilute collisionless suspension, EPL-Europhys. Lett., 78,
14001,
https://doi.org/10.1209/0295-5075/78/14001,
2007.
Bonadonna, C., Macedonio, G., and Sparks, R. S. J.: Numerical modelling of
tephra fallout associated with dome collapses and Vulcanian explosions:
application to hazard assessment on Montserrat, Geol. Soc. London, Mem., 21,
517–537, 2002.
Bürger, R. and Wendland, W. L.: Sedimentation and suspension flows:
historical perspective and some recent developments, J. Eng. Math., 41,
101–116,
https://doi.org/10.1023/A:1011934726111,
2001.
Bursik, M. I.: Effect of wind on the rise height of volcanic plumes,
Geophys. Res. Lett., 28, 3621–3624,
https://doi.org/10.1029/2001GL013393,
2001.
Carcano, S., Bonaventura, L., Esposti Ongaro, T., and Neri, A.: A
semi-implicit, second-order-accurate numerical model for multiphase
underexpanded volcanic jets, Geosci. Model Dev., 6, 1905–1924,
https://doi.org/10.5194/gmd-6-1905-2013, 2013.
Cerminara, M.: The Multiphase Buoyant Plume Solution of the Dusty Gas
Model, in preparation, ArXiV, available at:
http://arxiv.org/abs/1506.01638 (last access: 12 September 2015),
2015.
Cerminara, M.: Multiphase Flows in Volcanology, PhD thesis, Scuola
Normale Superiore, in preparation, 2016.
Cerminara, M., Berselli, L. C., Esposti Ongaro, T., and
Salvetti, M. V.: Direct numerical simulation of a compressible
multiphase flow through the Eulerian approach, in: Direct Large-Eddy
Simul. IX, edited by: Fröhlich, J., Kuerten, H., Geurts, B. J.,
and Armenio, V., ERCOFTAC Series, Springer, Switzerland, 2015.
Cerminara, M., Esposti Ongaro, T., and Neri, A.:
Large eddy simulation of gas–particle kinematic decoupling and turbulent
entrainment in volcanic plumes, J. Volcanol. Geoth. Res., submitted, 2016.
Chacón-Rebollo, T. and Lewandowski, R.: Mathematical and Numerical
Foundations of Turbulence Models, Birkhäuser, New-York, 2013.
Chai, X. and Mahesh, K.: Dynamic-equation model for large-eddy simulation of
compressible flows, J. Fluid Mech., 699, 385–413,
https://doi.org/10.1017/jfm.2012.115, 2012.
Cioni, R., Longo, A., Macedonio, G., Santacroce, R., Sbrana, A.,
Sulpizio, R., and Andronico, D.: Assessing pyroclastic fall hazard through
field data and numerical simulations: example from Vesuvius, J. Geophys.
Res.-Sol. Ea., 108, 1–11,
https://doi.org/10.1029/2001JB000642,
2003.
Clift, R., Grace, J., and Weber, M.: Bubbles, Drops, and Particles,
Academic Press, New York, San Francisco, London, 1978.
Costa A., Folch A., and Macedonio G.: Density-driven transport in the
umbrella region of volcanic clouds: Implications for tephra dispersion
models, Geophys. Res. Lett., 40, 4823–-4827,
https://doi.org/10.1002/grl.50942, 2013.
Costa, A., Suzuki, Y. J., Cerminara, M., Devenish, B. J., Esposti
Ongaro, T., Herzog, M., Van Eaton, A. R., Denby, L., Bursik, M. I., de'
Michieli Vitturi, M., Engwell, S., Neri, A., Barsotti, S., Folch, A.,
Macedonio, G., Girault, F., Carazzo, G., Tait, S., Kaminski, E.,
Mastin, L. G., Woodhouse, M. J., Phillips, J., Hogg, A. J., Degruyter, W.,
and Bonadonna, C.: Overview of the results of the eruption column model
inter-comparison exercise, J. Volcanol. Geoth. Res., submitted, 2015.
Culpo, M.: Current Bottlenecks in the Scalability of OpenFOAM on Massively
Parallel Clusters, Tech. rep., PRACE white papers, available at:
http://www.prace-ri.eu (last access: 14 October 2015), 2011.
Dagna, P.: OpenFOAM on BG/Q Porting and Performance, Tech. rep., CINECA,
available at:
http://www.training.prace-ri.eu/uploads/tx_pracetmo/OpenFOAM_on_BGQ_porting_and_performance.pdf
(last access: 14 October 2015), 2013.
Dartevelle, S., Rose, W. I., Stix, J., Kelfoun, K., and Vallance, J. W.:
Numerical modeling of geophysical granular flows: 2. Computer simulations of
plinian clouds and pyroclastic flows and surges, Geochem. Geophy. Geosy., 5,
Q08004,
https://doi.org/10.1029/2003GC000637,
2004.
Dellino, P., Mele, D., Bonasia, R., Braia, L., La Volpe, L., and
Sulpizio, R.: The analysis of the influence of pumice shape on its terminal
velocity, Geophys. Res. Lett., 32, L21306,
https://doi.org/10.1029/ 2005GL023954,
2005.
de' Michieli Vitturi, M., Neri, A., and Barsotti, S.: PLUME-MoM 1.0:
A new integral model of volcanic plumes based on the method of moments, Geosci. Model Dev., 8, 2447–2463,
https://doi.org/10.5194/gmd-8-2447-2015, 2015.
Di Muro, A., Neri, A., and Rosi, M.: Contemporaneous convective and
collapsing eruptive dynamics: the transitional regime of explosive
eruptions, Geophys. Res. Lett., 31, L10607, https://doi.org/10.1029/2004GL019709, 2004.
Dobran, F., Neri, A., and Macedonio, G.: Numerical simulation of collapsing
volcanic columns, J. Geophys. Res., 98, 4231–4259, 1993.
Ducros, F., Comte, P., and Lesieur, M.: Large-eddy simulation of a spatially
growing boundary layer over an adiabatic flat plate at low Mach number,
Int. J. Heat Fluid Flow, 16, 341–348, 1995.
Elghobashi, S.: Particle-laden turbulent flows: direct simulation and closure
models, Appl. Sci. Res., 48, 301–314, 1991.
Elghobashi, S.: On predicting particle-laden turbulent flows, Appl. Sci.
Res., 52, 309–329, 1994.
Erlebacher, G., Hussaini, M. Y., Speziale, C. G., and Zang, T. A.: Toward the
Large-Eddy Simulation of Compressible Turbulent Flows, ICASE Report 90-76,
Tech. rep., ICASE/NASA Langley Research Center, 1990.
Esposti Ongaro, T., Neri, A., Menconi, G., de' Michieli Vitturi, M.,
Marianelli, P., Cavazzoni, C., Erbacci, G., and Baxter, P. J.: Transient 3D
numerical simulations of column collapse and pyroclastic density current
scenarios at Vesuvius, J. Volcanol. Geotherm. Res., 178, 378–396, 2008.
Fanneløp, T. K. and Webber, D. M.: On buoyant plumes rising from area
sources in a calm environment, J. Fluid Mech., 497, 319–334,
https://doi.org/10.1017/S0022112003006669,
2003.
Feireisl, E.: Dynamics of Viscous Compressible Fluids, vol. 26 of Oxford
Lecture Series in Mathematics and its Applications, Oxford University Press,
Oxford, 212 pp., 2004.
Ferry, J. and Balachandar, S.: A fast Eulerian method for disperse two-phase
flow, Int. J. Multiph. Flow, 27, 1199–1226, https://doi.org/10.1016/S0301-9322(00)00069-0, 2001.
Ferry, J. and Balachandar, S.: Equilibrium expansion for the Eulerian
velocity of small particles, Powder Technol., 125, 131–139,
https://doi.org/10.1016/S0032-5910(01)00499-5,
2002.
Ferry, J. and Balachandar, S.: Equilibrium Eulerian approach for predicting
the thermal field of a dispersion of small particles, Int. J. Heat Mass
Trans., 48, 681–689,
https://doi.org/10.1016/j.ijheatmasstransfer.2004.07.047, 2005.
Ferry, J., Rani, S. L., and Balachandar, S.: A locally implicit improvement
of the equilibrium Eulerian method, Int. J. Multiph. Flow, 29, 869–891,
https://doi.org/10.1016/S0301-9322(03)00064-8,
2003.
Ferziger, J. H. and Perić, M.: Computational Methods for Fluid
Dynamics, Vol. 3, Springer, Berlin, 423 pp., 1996.
Folch, A., Costa, A., and Macedonio, G.: FPLUME-1.0: An integrated volcanic
plume model accounting for ash aggregation, Geosci. Model Dev. Discuss., 8,
8009–8062,
https://doi.org/10.5194/gmdd-8-8009-2015,
2015.
Fureby, C.: On subgrid scale modeling in large eddy simulations of
compressible fluid flow, Phys. Fluids, 8, 1301,
https://doi.org/10.1063/1.868900, 1996.
Ganser, G.: A rational approach to drag prediction of spherical and nonspherical particles, Powd. Tech., 77, 143152, 1993.
Garnier, E., Mossi, M., Sagaut, P., Comte, P., and Deville, M.: On the use
of shock-capturing schemes for large-Eddy simulation, J. Comput. Phys., 153,
273–311,
https://doi.org/10.1006/jcph.1999.6268,
1999.
Garnier, E., Sagaut, P., and Deville, M.: Large Eddy simulation of
shock/homogeneous turbulence interaction, Comput. Fluids, 31, 245–268,
https://doi.org/10.1016/S0045-7930(01)00022-6,
2002.
Garnier, E., Adams, N., and Sagaut, P.: Large Eddy Simulation for
Compressible Flows, https://doi.org/10.1007/978-90-481-2819-8, Springer, the
Netherlands, 276 pp., 2009.
George, W. K., Alpert, R. L., and Tamanini, F.: Turbulence measurements in
an axisymmetric buoyant plume, Int. J. Heat Mass Transf., 20, 1145–1154,
https://doi.org/10.1016/0017-9310(77)90123-5,
1977.
Germano, M., Piomelli, U., Moin, P., and Cabot, W. H.: A dynamic
subgrid-scale eddy viscosity model, Phys. Fluids A-Fluid, 3, 1760–1765,
1991.
Geurts, B. J. and Fröhlich, J.: A framework for predicting accuracy
limitations in large-eddy simulation, Phys. Fluids, 14, L41, https://doi.org/10.1063/1.1480830, 2002.
Gidaspow, D.: Multiphase Flow and Fluidization: Continuum and Kinetic Theory
Descriptions, Academic Press, San Diego, California, 1994.
Glaze, L. S. and Baloga, S. M.: Sensitivity of buoyant plume heights to
ambient atmospheric conditions: Implications for volcanic eruption
columns, J. Geophys. Res., 101, 1529–1540, 1996.
Graf, H.-F., Herzog, M., Oberhuber, J. M., and Textor, C.: Effect of
environmental conditions on volcanic plume rise, J. Geophys. Res., 104,
24309–24320, 1999.
Graham, T.: On the motion of gases, Philos. T. R. Soc., 136, 573–631,
1846.
Greenshields, C. J., Weller, H. G., Gasparini, L., and Reese, J. M.:
Implementation of semi-discrete, non-staggered central schemes in
a colocated, polyhedral, finite volume framework, for high-speed viscous
flows, Int. J. Numer. Methods Fluids, 63, 1–21,
https://doi.org/10.1002/fld.2069, 2010.
Hashimoto, A., Shimbori, T., and Fukui, K.: Tephra fall simulation for the
eruptions at Mt. Shinmoe-dake during 26–27 January 2011 with JMANHM, SOLA,
8, 37–40, 2012.
Honein, A. E. and Moin, P.: Higher entropy conservation and numerical
stability of compressible turbulence simulations, J. Comput. Phys., 201,
531–545,
https://doi.org/10.1016/j.jcp.2004.06.006,
2004.
Ishimine, Y.: Sensitivity of the dynamics of volcanic eruption columns to
their shape, Bull. Volcanol., 68, 516–537,
https://doi.org/10.1007/s00445-005-0027-4,
2006.
Issa, R. I.: Solution of the implicitly discretised fluid flow equations by
operator-splitting, J. Comput. Phys., 62, 40–65,
https://doi.org/10.1016/0021-9991(86)90099-9,
1986.
Jasak, H.: Error Analysis and Estimation for the Finite Volume Method with
Applications to Fluid Flows, PhD thesis, Imperial College London, 394 pp., 1996.
Kaminski, E. and Jaupart, C.: The size distribution of pyroclasts and the
fragmentation sequence in explosive volcanic eruptions, J. Geophys. Res.,
103, 29759,
https://doi.org/10.1029/98JB02795, 1998.
Kaminski, E., Tait, S., and Carazzo, G.: Turbulent entrainment in jets with
arbitrary buoyancy, J. Fluid Mech., 526, 361–376,
https://doi.org/10.1017/S0022112004003209,
2005.
Kay, D. A., Gresho, P. M., Griffiths, D. F., and Silvester, D. J.: Adaptive
time-stepping for incompressible flow part ii: Navier-stokes equations,
SIAM J. Sci. Comput., 32, 111–128, 2010.
Kieffer, S. W.: Factors governing the structure of volcanic jets, Explos.
Volcanism: Inception, Evol., Hazards, National Academy, Washington, 143–157, 1984.
Koyaguchi, T., Suzuki, Y. J., and Kozono, T.: Effects of the crater on
eruption column dynamics, J. Geophys. Res., 115, B07205, https://doi.org/10.1029/2009JB007146, 2010.
Kueppers, U., Perugini, D., and Dingwell, D. B.: “Explosive energy” during
volcanic eruptions from fractal analysis of pyroclasts, Earth Planet. Sci.
Lett., 248, 800–807, 2006.
Kurganov, A., Noelle, S., and Petrova, G.: Semidiscrete central-upwind
schemes for hyperbolic conservation laws and Hamilton–Jacobi equations,
SIAM J. Sci. Comput., 23, 707–740, 2001.
Lesieur, M., Métais, O., and Comte, P.: Large-Eddy Simulations of
Turbulence, Vol. 1, Cambridge University Press, 2005.
Liao, W., Peng, Y., and Luo, L.-S.: Gas-kinetic schemes for direct numerical
simulations of compressible homogeneous turbulence, Phys. Rev. E, 80,
046702,
https://doi.org/10.1103/PhysRevE.80.046702,
2009.
List, E. J.: Turbulent jets and plumes, Annu. Rev. Fluid Mech., 14,
189–212,
https://doi.org/10.1146/annurev.fl.14.010182.001201,
1982.
Lodato, G., Vervisch, L., and Domingo, P.: A compressible wall-adapting
similarity mixed model for large-eddy simulation of the impinging round jet,
Phys. Fluids, 21, 035102,
https://doi.org/10.1063/1.3068761, 2009.
Marble, F.: Dynamics of dusty gases, Annu. Rev. Fluid
Mech., 2, 397–446, https://doi.org/10.1146/annurev.fl.02.010170.002145, 1970.
Maxey, M. R.: The gravitational settling of aerosol particles in homogeneous
turbulence and random flow fields, J. Fluid Mech., 174, 441,
https://doi.org/10.1017/S0022112087000193,
1987.
Moin, P., Squires, K., Cabot, W., and Lee, S.: A dynamic subgrid-scale model
for compressible turbulence and scalar transport, Phys. Fluids A-Fluid, 3,
2746, https://doi.org/10.1063/1.858164, 1991.
Morrissey, M. M.: Burst conditions of explosive volcanic eruptions recorded
on microbarographs, Science, 275, 1290–1293,
https://doi.org/10.1126/science.275.5304.1290,
1997.
Morton, B. R.: Forced plumes, J. Fluid Mech., 5, 151–163, 1959.
Morton, B. R., Taylor, G., and Turner, J. S.: Turbulent gravitational
convection from maintained and instantaneous sources, P. R. Soc. A, 234,
1–23,
https://doi.org/10.1098/rspa.1956.0011,
1956.
Neri, A. and Dobran, F.: Influence of eruption parameters on the thermofluid
dynamics of collapsing volcanic columns, J. Geophys. Res., 99, 11833–11857,
https://doi.org/10.1029/94JB00471, 1994.
Neri, A., Esposti Ongaro, T., Macedonio, G., and Gidaspow, D.:
Multiparticle simulation of collapsing volcanic columns and pyroclastic
flow, J. Geophys. Res., 108, 2202,
https://doi.org/10.1029/2001JB000508,
2003.
Nicoud, F. and Ducros, F.: Subgrid-scale stress modelling based on
the square of the velocity gradient tensor, Flow
Turbul. Combust., 62, 183–200, https://doi.org/10.1023/A:1009995426001, 1999.
Oberhuber, J. M., Herzog, M., Graf, H.-F., and Schwanke, K.: Volcanic plume
simulation on large scales, J. Volcanol. Geoth. Res., 87, 29–53,
https://doi.org/10.1016/S0377-0273(98)00099-7,
1998.
Ogden, D. E., Glatzmaier, G. A., and Wohletz, K. H.: Effects of vent
overpressure on buoyant eruption columns: implications for plume stability,
Earth Planet Sc. Lett., 268, 283–292, 2008a.
Ogden, D. E., Wohletz, K. H., Glatzmaier, G. A., and Brodsky, E. E.:
Numerical simulations of volcanic jets: importance of vent overpressure, J.
Geophys. Res., 113, B02204,
https://doi.org/10.1029/2007JB005133,
2008b.
Orescanin, M. M., Austin, J. M., and Kieffer, S. W.: Unsteady high-pressure
flow experiments with applications to explosive volcanic eruptions, J.
Geophys. Res., 115, B06206,
https://doi.org/10.1029/2009JB006985, 2010.
Patankar, S. V.: Numerical Heat Transfer and Fluid Flow, Hemisphere
Publishing Corporation, New York, USA, 205 pp., 1980.
Pelanti, M. and LeVeque, R. J.: High-resolution finite volume methods for
dusty gas jets and plumes, SIAM J. Sci. Comput., 28, 1335–1360,
https://doi.org/10.1137/050635018, 2006.
Pfeiffer T., Costa A., Macedonio G.: A model for the numerical simulation of
tephra fall deposits, J. Volcanol. Geotherm. Res., 140, 273–294,
https://doi.org/10.1016/j.jvolgeores.2004.09.001,
2005.
Pirozzoli, S. and Grasso, F.: Direct numerical simulations of isotropic
compressible turbulence: influence of compressibility on dynamics and
structures, Phys. Fluids, 16, 4386,
https://doi.org/10.1063/1.1804553, 2004.
Piscaglia, F., Montorfano, A., and Onorati, A.: Towards the LES simulation
of IC engines with parallel topologically changing meshes, SAE Int. J.
Engines, 6, 926–940,
https://doi.org/10.4271/2013-01-1096,
2013.
Plourde, F., Pham, M. V., Kim, S. D., and Balachandar, S.: Direct numerical
simulations of a rapidly expanding thermal plume: structure and entrainment
interaction, J. Fluid Mech., 604, 99–123,
https://doi.org/10.1017/S0022112008001006,
2008.
Pope, S. B.: Turbulent Flows, Cambridge University Press, 771 pp., 2000.
Prandtl, L.: The Essentials of Fluid Dynamics, https://doi.org/10.1007/978-1-4419-1564-1, Blackie & Son
Limited, New York, 1963.
Rani, S. L. and Balachandar, S.: Evaluation of the equilibrium Eulerian
approach for the evolution of particle concentration in isotropic
turbulence, Int. J. Multiph. Flow, 29, 1793–1816,
https://doi.org/10.1016/j.ijmultiphaseflow.2003.09.005,
2003.
Ricou, F. P. and Spalding, D. B.: Measurements of entrainment by
axisymmetrical turbulent jets, J. Fluid Mech., 11, 21–32, 1961.
Sagaut, P.: Large Eddy Simulation for Incompressible Flows: an
Introduction, Springer Science & Business Media, Germany, 556 pp., 2006.
Scase, M. M.: Evolution of volcanic eruption columns, J. Geophys. Res.,
114, F04003, https://doi.org/10.1029/2009JF001300, 2009.
Shabbir, A. and George, W. K.: Experiments on a round turbulent buoyant
plume, J. Fluid Mech., 275, 1–32, 1994.
Shotorban, B. and Balachandar, S.: A Eulerian model for large-eddy
simulation of concentration of particles with small Stokes numbers, Phys.
Fluids, 19, 118107,
https://doi.org/10.1063/1.2804956, 2007.
Sod, G.: A survey of several of nonlinear finite difference methods
hyperbolic conservation laws, J. Comput. Phys., 27, 1–31, 1978.
Sparks, R. S. J.: The dynamics of bubble formation and growth in magmas:
a review and analysis, J. Volcanol. Geoth. Res., 3, 1–37, 1978.
Sparks, R. S. J., Bursik, M. I., Carey, S. N., Gilbert, J. S., Glaze, L. S.,
Sigurdsson, H., and Woods, A. W.: Volcanic Plumes, John Wiley, Chichester, 590 pp., 1997.
Suzuki, Y. J.: A numerical study of turbulent mixing in eruption clouds using
a three-dimensional fluid dynamics model, J. Geophys. Res., 110, B08201,
https://doi.org/10.1029/2004JB003460, 2005.
Suzuki, Y. J. and Koyaguchi, T.: Numerical determination of the efficiency
of
entrainment in volcanic eruption columns, Geophys. Res. Lett., 37,
L05302,
https://doi.org/10.1029/2009GL042159, 2010.
Suzuki, Y. J. and Koyaguchi, T.: 3D numerical simulation of volcanic
eruption clouds during the 2011 Shinmoe-dake eruptions, Earth Planets Space,
65, 581–589,
https://doi.org/10.5047/eps.2013.03.009,
2013.
Suzuki, Y. J., Costa, A., Cerminara, M., Esposti Ongaro, T., Herzog, M.,
Van Eaton, A., Denby, L. C.: Inter-comparison of three-dimensional models of
volcanic plumes, submitted to J. Volcanol. Geoth. Res., accepted, 2016.
Valentine, G. A. and Wohletz, K. H.: Numerical models of Plinian eruption
columns and pyroclastic flows, J. Geophys. Res., 94, 1867–1887, 1989.
Van Eaton, A. R., Mastin, L. G., Herzog, M., Schwaiger, H. F., Schneider,
D. J., Wallace, K. L., and Clarke, A. B.: Hail formation triggers rapid ash
aggregation in volcanic plumes, Nat. Commun., 6, 7860,
https://doi.org/10.1038/ncomms8860, 2015.
Van Leer, B.: Towards the ultimate conservative difference scheme, J.
Comput. Phys., 135, 229–248, 1997.
Veitch, G. and Woods, A. W.: Particle recycling in volcanic plumes, B.
Volcanol., 64, 31–39, 2002.
Vreman, A. W. A.: Direct and Large-Eddy Simulation of the Compressible
Turbulent Mixing Layer, PhD thesis, University of Twente, 1995.
Vuorinen, V., Keskinen, J. P., Duwig, C., and Boersma, B. J.: On the
implementation of low-dissipative Runge–Kutta projection methods for time
dependent flows using OpenFOAM, Comput. Fluids, 93, 153–163,
https://doi.org/10.1016/j.compfluid.2014.01.026,
2014.
Wang, L.-P. and Maxey, M. R.: Settling velocity and concentration
distribution of heavy particles in homogeneous isotropic turbulence, J.
Fluid Mech., 256, 27,
https://doi.org/10.1017/S0022112093002708,
1993.
Wilson, L.: Explosive volcanic eruptions – III – Plinian eruption
columns, Geophys. J. Roy. Astr. S., 45, 543–556, 1976.
Wilson, L.: Relationships between pressure, volatile content and ejecta
velocity in three types of volcanic explosion, J. Volcanol. Geoth. Res., 8,
297–313, 1980.
Wilson, L., Sparks, R. S. J., and Walker, G. P. L.: Explosive volcanic
eruptions – IV. The control of magma properties and conduit geometry on
eruption column behaviour, Geophys. J. Roy. Astr. S., 63, 117–148, 1980.
Woodhouse, M. J., Phillips, J. C., and Hogg, A. J.: Unsteady Turbulent
Buoyant Plumes, ArXiV, available at:
http://arxiv.org/abs/1507.06571 (last access: 23 July 2015), 2015.
Woods, A. W.: The fluid dynamics and thermodynamics of eruption columns,
Bull. Volcanol., 50, 169–193, 1988.
Woods, A. W.: Moist convection and the injection of volcanic ash into the
atmosphere, J. Geophys. Res., 98, 17617–17627, 1993.
Woods, A. W.: Turbulent plumes in nature, Annu. Rev. Fluid Mech., 42,
391–412,
https://doi.org/10.1146/annurev-fluid-121108-145430,
2010.
Woods, A. W. and Bower, S. M.: The decompression of volcanic jets in
a crater during explosive volcanic eruptions, Earth Planet. Sci. Lett., 131,
189–205, 1995.
Woods, A. W. and Bursik, M. I.: Particle fallout, thermal disequilibrium and
volcanic plumes, B. Volcanol., 53, 559–570, 1991.
Yoshizawa, A.: Statistical theory for compressible turbulent shear flows,
with the application to subgrid modeling, Phys. Fluids, 29, 2152,
https://doi.org/10.1063/1.865552, 1986.
Yoshizawa, A.: Bridging between eddy-viscosity-type and second-order
turbulence models through a two-scale turbulence theory, Phys. Rev. E, 48,
273–281,
https://doi.org/10.1103/PhysRevE.48.273,
1993.
Yüceil, K. B. and Ötügen, M. V.: Scaling parameters for
underexpanded supersonic jets, Phys. Fluids, 14, 4206, https://doi.org/10.1063/1.1513796, 2002.
Zhou, X., Luo, K. H., and Williams, J. J.: Large-eddy simulation of
a turbulent forced plume, Eur. J. Mech. B-Fluid., 20, 233–254,
https://doi.org/10.1016/S0997-7546(00)01117-1,
2001.
Short summary
A new model for gas–particles compressible turbulent dynamics is developed. It is implemented in a fluid dynamic code based on the OpenFOAM libraries. The solver is tested against well known benchmarks, in particular: single and multiphase isotropic turbulence, plume turbulent dynamics and shock tube experiments. These comparisons validate the capability of the solver to capture the desired physics. A volcanic plume is analyzed, focusing on non-equilibrium ash dynamics and mean plume properties.
A new model for gas–particles compressible turbulent dynamics is developed. It is implemented in...
