Articles | Volume 13, issue 11
https://doi.org/10.5194/gmd-13-5119-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-13-5119-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
30 Oct 2020
Development and technical paper |
| 30 Oct 2020
| 30 Oct 2020
Collisional growth in a particle-based cloud microphysical model: insights from column model simulations using LCM1D (v1.0)
Simon Unterstrasser
CORRESPONDING AUTHOR
Deutsches Zentrum für Luft- und Raumfahrt (DLR) – Institut für Physik der Atmosphäre, Oberpfaffenhofen, 82234 Wessling, Germany
Fabian Hoffmann
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO, USA
NOAA Earth System Research Laboratory (ESRL), Chemical Sciences Division, Boulder, CO, USA
Marion Lerch
Deutsches Zentrum für Luft- und Raumfahrt (DLR) – Institut für Physik der Atmosphäre, Oberpfaffenhofen, 82234 Wessling, Germany
Related authors
Andreas Bier, Simon Unterstrasser, Josef Zink, Dennis Hillenbrand, Tina Jurkat-Witschas, and Annemarie Lottermoser
Atmos. Chem. Phys., 24, 2319–2344, https://doi.org/10.5194/acp-24-2319-2024, https://doi.org/10.5194/acp-24-2319-2024, 2024
Short summary
Short summary
Using hydrogen as aviation fuel affects contrails' climate impact. We study contrail formation behind aircraft with H2 combustion. Due to the absence of soot emissions, contrail ice crystals are assumed to form only on ambient particles mixed into the plume. The ice crystal number, which strongly varies with temperature and aerosol number density, is decreased by more than 80 %–90 % compared to kerosene contrails. However H2 contrails can form at lower altitudes due to higher H2O emissions.
Michael A. Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas
Geosci. Model Dev., 15, 3879–3899, https://doi.org/10.5194/gmd-15-3879-2022, https://doi.org/10.5194/gmd-15-3879-2022, 2022
Short summary
Short summary
In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
Andreas Bier, Simon Unterstrasser, and Xavier Vancassel
Atmos. Chem. Phys., 22, 823–845, https://doi.org/10.5194/acp-22-823-2022, https://doi.org/10.5194/acp-22-823-2022, 2022
Short summary
Short summary
We investigate contrail formation in an aircraft plume with a particle-based multi-trajectory 0D model. Due to the high plume heterogeneity, contrail ice crystals form first near the plume edge and then in the plume centre. The number of ice crystals varies strongly with ambient conditions and soot properties near the contrail formation threshold. Our results imply that the multi-trajectory approach does not necessarily lead to improved scientific results compared to a single mean trajectory.
Simon Gruber, Simon Unterstrasser, Jan Bechtold, Heike Vogel, Martin Jung, Henry Pak, and Bernhard Vogel
Atmos. Chem. Phys., 18, 6393–6411, https://doi.org/10.5194/acp-18-6393-2018, https://doi.org/10.5194/acp-18-6393-2018, 2018
Short summary
Short summary
A numerical model also used for operational weather forecast was applied to investigate the impact of contrails and contrail cirrus on the radiative fluxes at the earth's surface. Accounting for contrails produced by aircraft enables the model to simulate high clouds that are otherwise missing. In a case study, we find that the effect of these extra clouds is to reduce the incoming shortwave radiation at the surface as well as the production of photovoltaic power by up to 10 %.
Simon Unterstrasser, Fabian Hoffmann, and Marion Lerch
Geosci. Model Dev., 10, 1521–1548, https://doi.org/10.5194/gmd-10-1521-2017, https://doi.org/10.5194/gmd-10-1521-2017, 2017
Short summary
Short summary
In the last decade, several Lagrangian microphysical models (LCMs) have been developed which use a large number of (computational) particles to represent a cloud. In particular, the collision process leading to coalescence of cloud droplets or aggregation of ice crystals is implemented differently in various models. Three existing implementations are reviewed and extended, and their performance is evaluated by a comparison with well established analytical and bin model solutions.
Simon Unterstrasser
Atmos. Chem. Phys., 16, 2059–2082, https://doi.org/10.5194/acp-16-2059-2016, https://doi.org/10.5194/acp-16-2059-2016, 2016
Short summary
Short summary
A large comprehensive data set of 3-D large eddy simulation (LES) of young contrails has been analysed.
Parametrisations of the most important properties of young contrails, namely the ice crystal number and geometric depth, are provided taking into account the effect of many environmental and aircraft parameters.
The parametrisation is suited to be incorporated in larger-scale models like GCMs.
S. Unterstrasser and I. Sölch
Geosci. Model Dev., 7, 695–709, https://doi.org/10.5194/gmd-7-695-2014, https://doi.org/10.5194/gmd-7-695-2014, 2014
S. Unterstrasser, R. Paoli, I. Sölch, C. Kühnlein, and T. Gerz
Atmos. Chem. Phys., 14, 2713–2733, https://doi.org/10.5194/acp-14-2713-2014, https://doi.org/10.5194/acp-14-2713-2014, 2014
Fabian Hoffmann, Franziska Glassmeier, and Graham Feingold
EGUsphere, https://doi.org/10.5194/egusphere-2024-1725, https://doi.org/10.5194/egusphere-2024-1725, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Clouds constitute a major cooling influence on Earth's climate system by reflecting a large fraction of the incident solar radiation back to space. This ability is controlled by the number of cloud droplets, which is governed by the number of aerosol particles in the atmosphere, laying out the foundation for so-called aerosol-cloud-climate interactions. In this study, a simple model to understand the effect of aerosol on cloud water is developed and applied.
Fan Yang, Hamed Fahandezh Sadi, Raymond A. Shaw, Fabian Hoffmann, Pei Hou, Aaron Wang, and Mikhail Ovchinnikov
EGUsphere, https://doi.org/10.5194/egusphere-2024-1693, https://doi.org/10.5194/egusphere-2024-1693, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Large-eddy simulations of a convection cloud chamber show two new microphysics regimes, cloud oscillation and cloud collapse, due to haze-cloud interactions. Our results suggest that haze particles and their interactions with cloud droplets should be considered especially in polluted conditions. To properly simulate haze-cloud interactions, we need to resolve droplet activation and deactivation processes, instead of using Twomey-type activation parameterization.
Yao-Sheng Chen, Jianhao Zhang, Fabian Hoffmann, Takanobu Yamaguchi, Franziska Glassmeier, Xiaoli Zhou, and Graham Feingold
EGUsphere, https://doi.org/10.5194/egusphere-2024-1033, https://doi.org/10.5194/egusphere-2024-1033, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Marine stratocumulus cloud is a type of shallow clouds that covers the vast areas of Earth's surface. They play an important role in Earth's energy balance by reflecting solar radiation back to space. We used numerical models to simulate a large number of marine stratocumuli with different characteristics. We found that how the clouds develop throughout the day is affected by the level of humidity in the air above the clouds and how closely the clouds connect to the ocean surface.
Andreas Bier, Simon Unterstrasser, Josef Zink, Dennis Hillenbrand, Tina Jurkat-Witschas, and Annemarie Lottermoser
Atmos. Chem. Phys., 24, 2319–2344, https://doi.org/10.5194/acp-24-2319-2024, https://doi.org/10.5194/acp-24-2319-2024, 2024
Short summary
Short summary
Using hydrogen as aviation fuel affects contrails' climate impact. We study contrail formation behind aircraft with H2 combustion. Due to the absence of soot emissions, contrail ice crystals are assumed to form only on ambient particles mixed into the plume. The ice crystal number, which strongly varies with temperature and aerosol number density, is decreased by more than 80 %–90 % compared to kerosene contrails. However H2 contrails can form at lower altitudes due to higher H2O emissions.
Prasanth Prabhakaran, Fabian Hoffmann, and Graham Feingold
Atmos. Chem. Phys., 24, 1919–1937, https://doi.org/10.5194/acp-24-1919-2024, https://doi.org/10.5194/acp-24-1919-2024, 2024
Short summary
Short summary
In this study, we explore the impact of deliberate aerosol perturbation in the northeast Pacific region using large-eddy simulations. Our results show that cloud reflectivity is sensitive to the aerosol sprayer arrangement in the pristine system, whereas in the polluted system it is largely proportional to the total number of aerosol particles injected. These insights would aid in assessing the efficiency of various aerosol injection strategies for climate intervention applications.
Edward Gryspeerdt, Franziska Glassmeier, Graham Feingold, Fabian Hoffmann, and Rebecca J. Murray-Watson
Atmos. Chem. Phys., 22, 11727–11738, https://doi.org/10.5194/acp-22-11727-2022, https://doi.org/10.5194/acp-22-11727-2022, 2022
Short summary
Short summary
The response of clouds to changes in aerosol remains a large uncertainty in our understanding of the climate. Studies typically look at aerosol and cloud processes in snapshot images, measuring all properties at the same time. Here we use multiple images to characterise how cloud temporal development responds to aerosol. We find a reduction in liquid water path with increasing aerosol, party due to feedbacks. This suggests the aerosol impact on cloud water may be weaker than in previous studies.
Michael A. Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas
Geosci. Model Dev., 15, 3879–3899, https://doi.org/10.5194/gmd-15-3879-2022, https://doi.org/10.5194/gmd-15-3879-2022, 2022
Short summary
Short summary
In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
Andreas Bier, Simon Unterstrasser, and Xavier Vancassel
Atmos. Chem. Phys., 22, 823–845, https://doi.org/10.5194/acp-22-823-2022, https://doi.org/10.5194/acp-22-823-2022, 2022
Short summary
Short summary
We investigate contrail formation in an aircraft plume with a particle-based multi-trajectory 0D model. Due to the high plume heterogeneity, contrail ice crystals form first near the plume edge and then in the plume centre. The number of ice crystals varies strongly with ambient conditions and soot properties near the contrail formation threshold. Our results imply that the multi-trajectory approach does not necessarily lead to improved scientific results compared to a single mean trajectory.
Björn Maronga, Sabine Banzhaf, Cornelia Burmeister, Thomas Esch, Renate Forkel, Dominik Fröhlich, Vladimir Fuka, Katrin Frieda Gehrke, Jan Geletič, Sebastian Giersch, Tobias Gronemeier, Günter Groß, Wieke Heldens, Antti Hellsten, Fabian Hoffmann, Atsushi Inagaki, Eckhard Kadasch, Farah Kanani-Sühring, Klaus Ketelsen, Basit Ali Khan, Christoph Knigge, Helge Knoop, Pavel Krč, Mona Kurppa, Halim Maamari, Andreas Matzarakis, Matthias Mauder, Matthias Pallasch, Dirk Pavlik, Jens Pfafferott, Jaroslav Resler, Sascha Rissmann, Emmanuele Russo, Mohamed Salim, Michael Schrempf, Johannes Schwenkel, Gunther Seckmeyer, Sebastian Schubert, Matthias Sühring, Robert von Tils, Lukas Vollmer, Simon Ward, Björn Witha, Hauke Wurps, Julian Zeidler, and Siegfried Raasch
Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020, https://doi.org/10.5194/gmd-13-1335-2020, 2020
Short summary
Short summary
In this paper, we describe the PALM model system 6.0. PALM is a Fortran-based turbulence-resolving code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. During the last years, PALM has been significantly improved and now offers a variety of new components that are especially designed to simulate the urban atmosphere at building-resolving resolution.
Franziska Glassmeier, Fabian Hoffmann, Jill S. Johnson, Takanobu Yamaguchi, Ken S. Carslaw, and Graham Feingold
Atmos. Chem. Phys., 19, 10191–10203, https://doi.org/10.5194/acp-19-10191-2019, https://doi.org/10.5194/acp-19-10191-2019, 2019
Short summary
Short summary
The climatic relevance of aerosol–cloud interactions depends on the sensitivity of the radiative effect of clouds to certain cloud properties. We derive the dependence of cloud fraction, cloud albedo, and the relative cloud radiative effect on the number of cloud droplets and on liquid water path from a large set of detailed simulations of stratocumulus clouds.
Maximilian Maahn, Fabian Hoffmann, Matthew D. Shupe, Gijs de Boer, Sergey Y. Matrosov, and Edward P. Luke
Atmos. Meas. Tech., 12, 3151–3171, https://doi.org/10.5194/amt-12-3151-2019, https://doi.org/10.5194/amt-12-3151-2019, 2019
Short summary
Short summary
Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Here, we present three novel methods for calibrating vertically pointing cloud radars. These calibration methods are based on microphysical processes of liquid clouds, such as the transition of cloud droplets to drizzle drops. We successfully apply the methods to cloud radar data from the North Slope of Alaska (NSA) and Oliktok Point (OLI) ARM sites.
Johannes Schwenkel, Fabian Hoffmann, and Siegfried Raasch
Geosci. Model Dev., 11, 3929–3944, https://doi.org/10.5194/gmd-11-3929-2018, https://doi.org/10.5194/gmd-11-3929-2018, 2018
Short summary
Short summary
Lagrangian cloud models are a powerful tool to understand cloud microphysics and are increasingly used in the cloud physics community. In this study we present a method designed to improve the warm cloud precipitation process in such models. Our results indicate that using this method is essential for a proper representation of the collisional process of warm clouds, while maintaining an appropriate computational demand.
Simon Gruber, Simon Unterstrasser, Jan Bechtold, Heike Vogel, Martin Jung, Henry Pak, and Bernhard Vogel
Atmos. Chem. Phys., 18, 6393–6411, https://doi.org/10.5194/acp-18-6393-2018, https://doi.org/10.5194/acp-18-6393-2018, 2018
Short summary
Short summary
A numerical model also used for operational weather forecast was applied to investigate the impact of contrails and contrail cirrus on the radiative fluxes at the earth's surface. Accounting for contrails produced by aircraft enables the model to simulate high clouds that are otherwise missing. In a case study, we find that the effect of these extra clouds is to reduce the incoming shortwave radiation at the surface as well as the production of photovoltaic power by up to 10 %.
Fabian Hoffmann
Atmos. Chem. Phys., 17, 8343–8356, https://doi.org/10.5194/acp-17-8343-2017, https://doi.org/10.5194/acp-17-8343-2017, 2017
Short summary
Short summary
This study analyzes at which aerosol radius the mass growth leading to activation switches from diffusion to collection, marking the limit of traditional Köhler activation theory. It is found that collection becomes increasingly important for aerosols larger than 0.1 µm in dry radius and is responsible for all activations of aerosols larger than 1.0 µm. A novel particle-based cloud modeling approach is applied, in which activation can be represented without parameterizations.
Simon Unterstrasser, Fabian Hoffmann, and Marion Lerch
Geosci. Model Dev., 10, 1521–1548, https://doi.org/10.5194/gmd-10-1521-2017, https://doi.org/10.5194/gmd-10-1521-2017, 2017
Short summary
Short summary
In the last decade, several Lagrangian microphysical models (LCMs) have been developed which use a large number of (computational) particles to represent a cloud. In particular, the collision process leading to coalescence of cloud droplets or aggregation of ice crystals is implemented differently in various models. Three existing implementations are reviewed and extended, and their performance is evaluated by a comparison with well established analytical and bin model solutions.
Simon Unterstrasser
Atmos. Chem. Phys., 16, 2059–2082, https://doi.org/10.5194/acp-16-2059-2016, https://doi.org/10.5194/acp-16-2059-2016, 2016
Short summary
Short summary
A large comprehensive data set of 3-D large eddy simulation (LES) of young contrails has been analysed.
Parametrisations of the most important properties of young contrails, namely the ice crystal number and geometric depth, are provided taking into account the effect of many environmental and aircraft parameters.
The parametrisation is suited to be incorporated in larger-scale models like GCMs.
B. Maronga, M. Gryschka, R. Heinze, F. Hoffmann, F. Kanani-Sühring, M. Keck, K. Ketelsen, M. O. Letzel, M. Sühring, and S. Raasch
Geosci. Model Dev., 8, 2515–2551, https://doi.org/10.5194/gmd-8-2515-2015, https://doi.org/10.5194/gmd-8-2515-2015, 2015
Short summary
Short summary
The paper gives a detailed description of the PArallelized Large-eddy simulation Model (PALM) version 4.0 for the simulation of turbulent atmospheric and oceanic boundary layer flows. The model is optimized for use on massively parallel computer architectures and has been applied for various boundary-layer research studies over the last 15 years by various work groups all over the world. Besides the model description, we outline past PALM applications and also discuss future perspectives.
S. Unterstrasser and I. Sölch
Geosci. Model Dev., 7, 695–709, https://doi.org/10.5194/gmd-7-695-2014, https://doi.org/10.5194/gmd-7-695-2014, 2014
S. Unterstrasser, R. Paoli, I. Sölch, C. Kühnlein, and T. Gerz
Atmos. Chem. Phys., 14, 2713–2733, https://doi.org/10.5194/acp-14-2713-2014, https://doi.org/10.5194/acp-14-2713-2014, 2014
Related subject area
Atmospheric sciences
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
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
TAMS: A Tracking, Classifying, and Variable-Assigning Algorithm for Mesoscale Convective Systems in Simulated and Satellite-Derived Datasets
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
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.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
Short summary
Short summary
PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Kelly M. Núñez Ocasio and Zachary L. Moon
EGUsphere, https://doi.org/10.5194/egusphere-2024-259, https://doi.org/10.5194/egusphere-2024-259, 2024
Short summary
Short summary
TAMS is an open-source mesoscale convective system tracking and classifying Python-based package that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
Short summary
Short summary
Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
Short summary
Short summary
Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Cited articles
Alfonso, L. and Raga, G. B.: The impact of fluctuations and correlations in droplet growth by collision–coalescence revisited – Part 1: Numerical calculation of post-gel droplet size distribution, Atmos. Chem. Phys., 17, 6895–6905, https://doi.org/10.5194/acp-17-6895-2017, 2017. a, b
Alfonso, L., Raga, G. B., and Baumgardner, D.: The validity of the kinetic collection equation revisited, Atmos. Chem. Phys., 8, 969–982, https://doi.org/10.5194/acp-8-969-2008, 2008. a
Andrejczuk, M., Reisner, J. M., Henson, B., Dubey, M. K., and Jeffery, C. A.:
The potential impacts of pollution on a nondrizzling stratus deck: Does
aerosol number matter more than type?, J. Geophys. Res., 113, D19204,
https://doi.org/10.1029/2007JD009445, 2008. a
Andrejczuk, M., Grabowski, W. W., Reisner, J., and Gadian, A.: Cloud-aerosol
interactions for boundary layer stratocumulus in the Lagrangian cloud model,
J. Geophys. Res., 115, D22214, https://doi.org/10.1029/2010JD014248, 2010. a
Arabas, S., Jaruga, A., Pawlowska, H., and Grabowski, W. W.: libcloudph++ 1.0: a single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in C++, Geosci. Model Dev., 8, 1677–1707, https://doi.org/10.5194/gmd-8-1677-2015, 2015. a, b
Arnason, G. and Brown, Philip S., J.: Growth of Cloud Droplets by
Condensation: A Problem in Computational Stability, J. Atmos. Sci., 28,
72–77, https://doi.org/10.1175/1520-0469(1971)028<0072:GOCDBC>2.0.CO;2, 1971. a
Bayewitz, M. H., Yerushalmi, J., Katz, S., and Shinnar, R.: The Extent of
Correlations in a Stochastic Coalescence Process, J. Atmos. Sci., 31,
1604–1614, https://doi.org/10.1175/1520-0469(1974)031<1604:TEOCIA>2.0.CO;2, 1974. a, b, c, d
Beard, K. V.: Terminal Velocity and Shape of Cloud and Precipitation Drops
Aloft, J. Atmos. Sci., 33, 851–864,
https://doi.org/10.1175/1520-0469(1976)033<0851:TVASOC>2.0.CO;2, 1976. a
Beard, K. V. and Ochs III, H. T.: Collection and coalescence efficiencies for
accretion., J. Geophys. Res., 89, 7165–7169, https://doi.org/10.1029/JD089iD05p07165,
1984. a
Berry, E. X.: Cloud Droplet Growth by Collection, J. Atmos. Sci., 24,
688–701, https://doi.org/10.1175/1520-0469(1967)024<0688:CDGBC>2.0.CO;2, 1967. a, b, c
Berry, E. X. and Reinhardt, R. L.: An Analysis of Cloud Drop Growth by
Collection: Part I. Double Distributions, J. Atmos. Sci., 31, 1814–1824,
https://doi.org/10.1175/1520-0469(1974)031<1814:AAOCDG>2.0.CO;2, 1974. a
Bott, A.: A Flux Method for the Numerical Solution of the Stochastic Collection
Equation: Extension to Two-Dimensional Particle Distributions, J. Atmos.
Sci., 57, 284–294, https://doi.org/10.1175/1520-0469(2000)057<0284:AFMFTN>2.0.CO;2,
2000. a
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and aerosols, in: Climate change 2013: the physical science basis. Contribution
of Working Group I to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, Cambridge University Press, 571–657, 2013. a
Dziekan, P., Waruszewski, M., and Pawlowska, H.: University of Warsaw Lagrangian Cloud Model (UWLCM) 1.0: a modern large-eddy simulation tool for warm cloud modeling with Lagrangian microphysics, Geosci. Model Dev., 12, 2587–2606, https://doi.org/10.5194/gmd-12-2587-2019, 2019. a, b
Gillespie, D. T.: The Stochastic Coalescence Model for Cloud Droplet Growth, J. Atmos. Sci., 29, 1496–1510,
https://doi.org/10.1175/1520-0469(1972)029<1496:TSCMFC>2.0.CO;2, 1972. a, b, c
Grabowski, W. W., Morrison, H., Shima, S.-i., Abade, G. C., Dziekan, P., and Pawlowska, H.: Modeling of Cloud Microphysics: Can We Do Better?, B. Am. Meteorol. Soc., 100, 655–672, https://doi.org/10.1175/BAMS-D-18-0005.1, 2019. a
Hall, W. D.: A Detailed Microphysical Model Within a Two-Dimensional Dynamic
Framework: Model Description and Preliminary Results, J. Atmos. Sci., 37,
2486–2507, https://doi.org/10.1175/1520-0469(1980)037<2486:ADMMWA>2.0.CO;2, 1980. a, b
Hoffmann, F. and Feingold, G.: Entrainment and Mixing in Stratocumulus:
Effects of a New Explicit Subgrid-Scale Scheme for Large-Eddy Simulations
with Particle-Based Microphysics, J. Atmos. Sci., 76, 1955–1973,
https://doi.org/10.1175/JAS-D-18-0318.1, 2019. a
Hoffmann, F., Yamaguchi, T., and Feingold, G.: Inhomogeneous Mixing in
Lagrangian Cloud Models: Effects on the Production of Precipitation Embryos, J. Atmos. Sci., 76, 113–133, https://doi.org/10.1175/JAS-D-18-0087.1, 2019. a, b
Hu, Z. and Srivastava, R. C.: Evolution of Raindrop Size Distribution by
Coalescence, Breakup, and Evaporation: Theory and Observations, J. Atmos.
Sci., 52, 1761–1783, https://doi.org/10.1175/1520-0469(1995)052<1761:EORSDB>2.0.CO;2,
1995. a, b
Kessler, E.: On distribution and continuity of water substance in atmospheric
circulations, Mon. Am. Meteorol. Soc., 10, 1–84,
https://doi.org/10.1007/978-1-935704-36-2_1, 1969. a
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, https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2, 2000. a
Kostinski, A. and Shaw, R.: Fluctuations and luck in droplet growth by
coalescence, B. Am. Meteorol. Soc., 86, 235–244,
https://doi.org/10.1175/BAMS-86-2-235, 2005. a, b
Krueger, S. K. and Kerstein, A. R.: An Economical Model for Simulating
Turbulence Enhancement of Droplet Collisions and Coalescence, J. Adv. Model.
Earth Sy., 10, 1858–1881, https://doi.org/10.1029/2017MS001240, 2018. a
L'Ecuyer, P. and Simard, R.: TestU01: A C Library for Empirical Testing of
Random Number Generators, ACM Trans. Math. Softw., 33, 22,
https://doi.org/10.1145/1268776.1268777, 2007. a
List, R., Donaldson, N. R., and Stewart, R. E.: Temporal Evolution of Drop
Spectra to Collisional Equilibrium in Steady and Pulsating Rain, J. Atmos.
Sci., 44, 362–372, https://doi.org/10.1175/1520-0469(1987)044<0362:TEODST>2.0.CO;2,
1987. a
Long, A. B.: Solutions to the Droplet Collection Equation for Polynomial
Kernels, J. Atmos. Sci., 31, 1040–1052,
https://doi.org/10.1175/1520-0469(1974)031<1040:STTDCE>2.0.CO;2, 1974. a, b
Matsumoto, M. and Nishimura, T.: Mersenne Twister: a 623-dimensionally
equidistributed uniform pseudo-random number generator, ACM T. Model. Comput. S., 8, 3–30, https://doi.org/10.1145/272991.272995,
1998. a
Naumann, A. K. and Seifert, A.: A Lagrangian drop model to study warm rain
microphysical processes in shallow cumulus, J. Adv. Model. Earth Sy., 7,
1136–1154, https://doi.org/10.1002/2015MS000456, 2015. a
Ochs III, H. T. and Beard, K. V.: Laboratory measurements of collection
efficiencies for accretion, J. Atmos. Sci., 41, 863–867,
https://doi.org/10.1175/1520-0469(1984)041<0863:LMOCEF>2.0.CO;2, 1984. a
Prat, O. P. and Barros, A. P.: Exploring the use of a column model for the characterization of microphysical processes in warm rain: results from a homogeneous rainshaft model, Adv. Geosci., 10, 145–152, https://doi.org/10.5194/adgeo-10-145-2007, 2007. a, b
Riechelmann, T., Noh, Y., and Raasch, S.: A new method for large-eddy
simulations of clouds with Lagrangian droplets including the effects of
turbulent collision, New J. Phys., 14, 065008,
https://doi.org/10.1088/1367-2630/14/6/065008, 2012. a, b
Saffman, P. G. and Turner, J. S.: On the collision of drops in turbulent
clouds, J. Fluid Mech., 1, 16–30, https://doi.org/10.1017/S0022112056000020, 1956. a
Schwenkel, J., Hoffmann, F., and Raasch, S.: Improving collisional growth in Lagrangian cloud models: development and verification of a new splitting algorithm, Geosci. Model Dev., 11, 3929–3944, https://doi.org/10.5194/gmd-11-3929-2018, 2018. a, b
Seifert, A.: On the Parameterization of Evaporation of Raindrops as Simulated
by a One-Dimensional Rainshaft Model, J. Atmos. Sci., 65, 3608–3619,
https://doi.org/10.1175/2008JAS2586.1, 2008. a
Seifert, A. and Beheng, K. D.: A double-moment parameterization for simulating
autoconversion, accretion and selfcollection, Atmos. Res., 59, 265–281,
https://doi.org/10.1016/S0169-8095(01)00126-0, 2001. a
Shima, S., Kusano, K., Kawano, A., Sugiyama, T., and Kawahara, S.: The
super-droplet method for the numerical simulation of clouds and
precipitation: a particle-based and probabilistic microphysics model coupled
with a non-hydrostatic model, Q. J. R. Meteor. Soc., 135, 1307–1320,
https://doi.org/10.1002/qj.441, 2009. a, b, c, d, e, f, g, h, i, j, k
Shima, S., Sato, Y., Hashimoto, A., and Misumi, R.: Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2, Geosci. Model Dev., 13, 4107–4157, https://doi.org/10.5194/gmd-13-4107-2020, 2020. a, b, c
Simmel, M., Trautmann, T., and Tetzlaff, G.: Numerical solution of the
stochastic collection equation - comparison of the Linear Discrete Method
with other methods, Atmos. Res., 61, 135–148,
https://doi.org/10.1016/S0169-8095(01)00131-4, 2002. a
Smolarkiewicz, P. and Margolin, L.: MPDATA: A Finite-Difference Solver for
Geophysical Flows, J. Comput. Phys., 140, 459–480, 1998. a
Smolarkiewicz, P. K.: A fully multidimensional positive definite advection
transport algorithm with small implicit diffusion, J. Comput. Phys., 54,
325–362, https://doi.org/10.1016/0021-9991(84)90121-9, 1984. a, b
Smolarkiewicz, P. K.: Multidimensional positive definite advection transport
algorithm: an overview, Int. J. Numer. Methods Fluids, 50, 1123–1144,
https://doi.org/10.1002/fld.1071, 2006. a
Smoluchowski, M. V.: Drei Vortrage über Diffusion, Brownsche Bewegung und Koagulation von Kolloidteilchen, Z. Phys., 17, 557–571,
1916. a
Stevens, B. and Seifert, A.: Understanding macrophysical outcomes of
microphysical choices in simulations of shallow cumulus convection, J. Meteorol. Soc. Jpn. Ser. II, 86A, 143–162,
https://doi.org/10.2151/jmsj.86A.143, 2008. a, b
Telford, J. W.: A new aspect of coalescence theory, J. Meteorol., 12,
436–444, https://doi.org/10.1175/1520-0469(1955)012<0436:ANAOCT>2.0.CO;2, 1955. a
Tzivion, S., Feingold, G., and Levin, Z.: An Efficient Numerical Solution to the Stochastic Collection Equation, J. Atmos. Sci., 44, 3139–3149,
https://doi.org/10.1175/1520-0469(1987)044<3139:AENSTT>2.0.CO;2, 1987. a
Tzivion (Tzitzvashvili), 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,
https://doi.org/10.1175/1520-0469(1989)046<3312:TEORSP>2.0.CO;2, 1989.
a
Unterstrasser, S.: SimonUnterstrasser/ColumnModel: GMD release, Zenodo, https://doi.org/10.5281/zenodo.4031214, 2020a. a
Unterstrasser, S.: Simulation/Plot Data of collisional growth column model, Zenodo, https://doi.org/10.5281/zenodo.4030878, 2020b. a
Unterstrasser, S., Hoffmann, F., and Lerch, M.: Collection/aggregation algorithms in Lagrangian cloud microphysical models: rigorous evaluation in box model simulations, Geosci. Model Dev., 10, 1521–1548, https://doi.org/10.5194/gmd-10-1521-2017, 2017. a, b, c
Wang, L.-P., Wexler, A. S., and Zhou, Y.: Statistical mechanical descriptions of turbulent coagulation, Phys. Fluid., 10, 2647–2651,
https://doi.org/10.1063/1.869777, 1998. a
Wang, L.-P., Ayala, O., and Xue, Y.: Reconciling the cylindrical formulation with the spherical formulation in the kinematic descriptions of collision
kernel, Phys. Fluid., 17, 067103, https://doi.org/10.1063/1.1928647, 2005. a
Wang, L.-P., Xue, Y., Ayala, O., and Grabowski, W. W.: Effects of stochastic coalescence and air turbulence on the size distribution of cloud droplets, Atmos. Res., 82, 416–432, https://doi.org/10.1063/1.1928647, 2006. a, b, c
Short summary
Particle-based cloud models use simulation particles for the representation of cloud particles like droplets or ice crystals. The collision and merging of cloud particles (i.e. collisional growth a.k.a. collection in the case of cloud droplets and aggregation in the case of ice crystals) was found to be a numerically challenging process in such models. The study presents verification exercises in a 1D column model, where sedimentation and collisional growth are the only active processes.
Particle-based cloud models use simulation particles for the representation of cloud particles...
