Articles | Volume 10, issue 4
Geosci. Model Dev., 10, 1521–1548, 2017
https://doi.org/10.5194/gmd-10-1521-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: Particle-based methods for simulating atmospheric aerosol...
Geosci. Model Dev., 10, 1521–1548, 2017
https://doi.org/10.5194/gmd-10-1521-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper 13 Apr 2017
Model evaluation paper | 13 Apr 2017
Collection/aggregation algorithms in Lagrangian cloud microphysical models: rigorous evaluation in box model simulations
Simon Unterstrasser et al.
Related authors
Andreas Bier, Simon Unterstrasser, and Xavier Vancassel
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-361, https://doi.org/10.5194/acp-2021-361, 2021
Preprint under review for ACP
Short summary
Short summary
We investigate the contrail formation in an aircraft plume with a particle-based 0D model. The mixing of the exhaust with ambient air leads to a strong plume variability. Therefore, contrail ice crystals form first near the plume edge and then in the plume centre. The number of formed ice crystals varies strongly with ambient conditions and certain soot properties only near the contrail formation threshold. Our results show a good agreement with a recent study using similar microphysics.
Michael Olesik, Sylwester Arabas, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, and Simon Unterstrasser
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-404, https://doi.org/10.5194/gmd-2020-404, 2021
Preprint under review for GMD
Simon Unterstrasser, Fabian Hoffmann, and Marion Lerch
Geosci. Model Dev., 13, 5119–5145, https://doi.org/10.5194/gmd-13-5119-2020, https://doi.org/10.5194/gmd-13-5119-2020, 2020
Short summary
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.
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
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
Andreas Bier, Simon Unterstrasser, and Xavier Vancassel
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-361, https://doi.org/10.5194/acp-2021-361, 2021
Preprint under review for ACP
Short summary
Short summary
We investigate the contrail formation in an aircraft plume with a particle-based 0D model. The mixing of the exhaust with ambient air leads to a strong plume variability. Therefore, contrail ice crystals form first near the plume edge and then in the plume centre. The number of formed ice crystals varies strongly with ambient conditions and certain soot properties only near the contrail formation threshold. Our results show a good agreement with a recent study using similar microphysics.
Michael Olesik, Sylwester Arabas, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, and Simon Unterstrasser
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-404, https://doi.org/10.5194/gmd-2020-404, 2021
Preprint under review for GMD
Simon Unterstrasser, Fabian Hoffmann, and Marion Lerch
Geosci. Model Dev., 13, 5119–5145, https://doi.org/10.5194/gmd-13-5119-2020, https://doi.org/10.5194/gmd-13-5119-2020, 2020
Short summary
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.
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
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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
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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
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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
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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
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
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Efficient ensemble generation for uncertain correlated parameters in atmospheric chemical models: a case study for biogenic emissions from EURAD-IM version 5
Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0
Atmosphere–ocean–aerosol–chemistry–climate model SOCOLv4.0: description and evaluation
Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models
Mesoscale nesting interface of the PALM model system 6.0
Multi-sensor analyses of the skin temperature for the assimilation of satellite radiances in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS, cycle 47R1)
The Grell–Freitas (GF) convection parameterization: recent developments, extensions, and applications
Calibrating a global atmospheric chemistry transport model using Gaussian process emulation and ground-level concentrations of ozone and carbon monoxide
The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies
Modeling of land–surface interactions in the PALM model system 6.0: land surface model description, first evaluation, and sensitivity to model parameters
Improvements to the representation of BVOC chemistry–climate interactions in UKCA (v11.5) with the CRI-Strat 2 mechanism: incorporation and evaluation
Extension of a gaseous dry deposition algorithm to oxidized volatile organic compounds and hydrogen cyanide for application in chemistry transport models
iNRACM: incorporating 15N into the Regional Atmospheric Chemistry Mechanism (RACM) for assessing the role photochemistry plays in controlling the isotopic composition of NOx, NOy, and atmospheric nitrate
Latent Linear Adjustment Autoencoder v1.0: a novel method for estimating and emulating dynamic precipitation at high resolution
Validation of the PALM model system 6.0 in a real urban environment: a case study in Dejvice, Prague, the Czech Republic
Data reduction for inverse modeling: an adaptive approach v1.0
Comparison of source apportionment approaches and analysis of non-linearity in a real case model application
APFoam 1.0: integrated computational fluid dynamics simulation of O3–NOx–volatile organic compound chemistry and pollutant dispersion in a typical street canyon
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Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): organization and experimental design
Sensitivity analysis of the PALM model system 6.0 in the urban environment
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Oxidation of low-molecular-weight organic compounds in cloud droplets: development of the Jülich Aqueous-phase Mechanism of Organic Chemistry (JAMOC) in CAABA/MECCA (version 4.5.0)
Prediction of source contributions to urban background PM10 concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 – Part 2: The city contribution
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Annika Vogel and Hendrik Elbern
Geosci. Model Dev., 14, 5583–5605, https://doi.org/10.5194/gmd-14-5583-2021, https://doi.org/10.5194/gmd-14-5583-2021, 2021
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While atmospheric chemical forecasts rely on uncertain model parameters, their huge dimensions hamper an efficient uncertainty estimation. This study presents a novel approach to efficiently sample these uncertainties by extracting dominant dependencies and correlations. Applying the algorithm to biogenic emissions, their uncertainties can be estimated from a low number of dominant components. This states the capability of an efficient treatment of parameter uncertainties in atmospheric models.
Jianbing Jin, Arjo Segers, Hai Xiang Lin, Bas Henzing, Xiaohui Wang, Arnold Heemink, and Hong Liao
Geosci. Model Dev., 14, 5607–5622, https://doi.org/10.5194/gmd-14-5607-2021, https://doi.org/10.5194/gmd-14-5607-2021, 2021
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When discussing the accuracy of a dust forecast, the shape and position of the plume as well as the intensity are key elements. The position forecast determines which locations will be affected, while the intensity only describes the actual dust level. A dust forecast with position misfit directly results in incorrect timing profiles of dust loads. In this paper, an image-morphing-based data assimilation is designed for realigning a simulated dust plume to correct for the position error.
Timofei Sukhodolov, Tatiana Egorova, Andrea Stenke, William T. Ball, Christina Brodowsky, Gabriel Chiodo, Aryeh Feinberg, Marina Friedel, Arseniy Karagodin-Doyennel, Thomas Peter, Jan Sedlacek, Sandro Vattioni, and Eugene Rozanov
Geosci. Model Dev., 14, 5525–5560, https://doi.org/10.5194/gmd-14-5525-2021, https://doi.org/10.5194/gmd-14-5525-2021, 2021
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This paper features the new atmosphere–ocean–aerosol–chemistry–climate model SOCOLv4.0 and its validation. The model performance is evaluated against reanalysis products and observations of atmospheric circulation and trace gas distribution, with a focus on stratospheric processes. Although we identified some problems to be addressed in further model upgrades, we demonstrated that SOCOLv4.0 is already well suited for studies related to chemistry–climate–aerosol interactions.
Haipeng Lin, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Christoph A. Keller, Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Patrick C. Campbell, Barry Baker, Rick D. Saylor, and Raffaele Montuoro
Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021, https://doi.org/10.5194/gmd-14-5487-2021, 2021
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Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to select, add, and scale emissions from different sources through a configuration file with no change to the model source code. We demonstrate the implementation of HEMCO in several models, all sharing the same HEMCO core code and database library.
Eckhard Kadasch, Matthias Sühring, Tobias Gronemeier, and Siegfried Raasch
Geosci. Model Dev., 14, 5435–5465, https://doi.org/10.5194/gmd-14-5435-2021, https://doi.org/10.5194/gmd-14-5435-2021, 2021
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In this paper, we provide a technical description of a newly developed interface for coupling the PALM model system 6.0 to the weather prediction model COSMO. The interface allows users of PALM to simulate the detailed atmospheric flow for relatively small regions of tens of kilometres under specific weather conditions, for instance, periods around observation campaigns or extreme weather situations. We demonstrate the interface using a benchmark simulation.
Sebastien Massart, Niels Bormann, Massimo Bonavita, and Cristina Lupu
Geosci. Model Dev., 14, 5467–5485, https://doi.org/10.5194/gmd-14-5467-2021, https://doi.org/10.5194/gmd-14-5467-2021, 2021
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Numerical weather predictions combine data from satellites with atmospheric forecasts. Some satellites measure the radiance emitted by the Earth's surface. To use this data, one must have knowledge of the surface properties, like the temperature of the thin layer above the surface. Error in this temperature leads to a misuse of the satellite data and affects the quality of the weather forecast. We updated our approach to better estimate this temperature, which should help improve the forecast.
Saulo R. Freitas, Georg A. Grell, and Haiqin Li
Geosci. Model Dev., 14, 5393–5411, https://doi.org/10.5194/gmd-14-5393-2021, https://doi.org/10.5194/gmd-14-5393-2021, 2021
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Convection parameterization (CP) is a component of atmospheric models aiming to represent the statistical effects of subgrid-scale convective clouds. Because the atmosphere contains circulations with a broad spectrum of scales, the truncation needed to run models in computers requires the introduction of parameterizations to account for processes that are not explicitly resolved. We detail recent developments in the Grell–Freitas CP, which has been applied in several regional and global models.
Edmund Ryan and Oliver Wild
Geosci. Model Dev., 14, 5373–5391, https://doi.org/10.5194/gmd-14-5373-2021, https://doi.org/10.5194/gmd-14-5373-2021, 2021
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Atmospheric chemistry transport models are important tools to investigate the local, regional and global controls on atmospheric composition and air quality. In this study, we estimate some of the model parameters using machine learning and statistics. Our findings identify the level of error and spatial coverage in the O2 and CO data that are needed to achieve good parameter estimates. We also highlight the benefits of using multiple constraints to calibrate atmospheric chemistry models.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
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We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Katrin Frieda Gehrke, Matthias Sühring, and Björn Maronga
Geosci. Model Dev., 14, 5307–5329, https://doi.org/10.5194/gmd-14-5307-2021, https://doi.org/10.5194/gmd-14-5307-2021, 2021
James Weber, Scott Archer-Nicholls, Nathan Luke Abraham, Youngsub M. Shin, Thomas J. Bannan, Carl J. Percival, Asan Bacak, Paulo Artaxo, Michael Jenkin, M. Anwar H. Khan, Dudley E. Shallcross, Rebecca H. Schwantes, Jonathan Williams, and Alex T. Archibald
Geosci. Model Dev., 14, 5239–5268, https://doi.org/10.5194/gmd-14-5239-2021, https://doi.org/10.5194/gmd-14-5239-2021, 2021
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The new mechanism CRI-Strat 2 features state-of-the-art isoprene chemistry not previously available in UKCA and improves UKCA's ability to reproduce observed concentrations of isoprene, monoterpenes, and OH in tropical regions. The enhanced ability to model isoprene, the most widely emitted non-methane volatile organic compound (VOC), will allow understanding of how isoprene and other biogenic VOCs affect atmospheric composition and, through biosphere–atmosphere feedbacks, climate change.
Zhiyong Wu, Leiming Zhang, John T. Walker, Paul A. Makar, Judith A. Perlinger, and Xuemei Wang
Geosci. Model Dev., 14, 5093–5105, https://doi.org/10.5194/gmd-14-5093-2021, https://doi.org/10.5194/gmd-14-5093-2021, 2021
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A community dry deposition algorithm for modeling the gaseous dry deposition process in chemistry transport models was extended to include an additional 12 oxidized volatile organic compounds and hydrogen cyanide based on their physicochemical properties and was then evaluated using field flux measurements over a mixed forest. This study provides a useful tool that is needed in chemistry transport models with increasing complexity for simulating an important atmospheric process.
Huan Fang, Wendell W. Walters, David Mase, and Greg Michalski
Geosci. Model Dev., 14, 5001–5022, https://doi.org/10.5194/gmd-14-5001-2021, https://doi.org/10.5194/gmd-14-5001-2021, 2021
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A new photochemical reaction scheme that incorporates nitrogen isotopes has been developed to simulate isotope tracers in air pollution. The model contains 16 N compounds, and 96 reactions involving N used in the Regional Atmospheric Chemistry Mechanism (RACM) were replicated using 15N in a new mechanism called iNRACM. The model is able to predict d15N variations in NOx, HONO, and HNO3 that are similar to those observed in aerosol and gases in the troposphere.
Christina Heinze-Deml, Sebastian Sippel, Angeline G. Pendergrass, Flavio Lehner, and Nicolai Meinshausen
Geosci. Model Dev., 14, 4977–4999, https://doi.org/10.5194/gmd-14-4977-2021, https://doi.org/10.5194/gmd-14-4977-2021, 2021
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Quantifying dynamical and thermodynamical components of regional precipitation change is a key challenge in climate science. We introduce a novel statistical model (Latent Linear Adjustment Autoencoder) that combines the flexibility of deep neural networks with the robustness advantages of linear regression. The method enables estimation of the contribution of a coarse-scale atmospheric circulation proxy to daily precipitation at high resolution and in a spatially coherent manner.
Jaroslav Resler, Kryštof Eben, Jan Geletič, Pavel Krč, Martin Rosecký, Matthias Sühring, Michal Belda, Vladimír Fuka, Tomáš Halenka, Peter Huszár, Jan Karlický, Nina Benešová, Jana Ďoubalová, Kateřina Honzáková, Josef Keder, Šárka Nápravníková, and Ondřej Vlček
Geosci. Model Dev., 14, 4797–4842, https://doi.org/10.5194/gmd-14-4797-2021, https://doi.org/10.5194/gmd-14-4797-2021, 2021
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We describe validation of the PALM model v6.0 against measurements collected during two observational campaigns in Dejvice, Prague. The study focuses on the evaluation of the newly developed or improved radiative and energy balance modules in PALM related to urban modelling. In addition to the energy-related quantities, it also evaluates air flow and air quality under street canyon conditions.
Xiaoling Liu, August L. Weinbren, He Chang, Jovan M. Tadić, Marikate E. Mountain, Michael E. Trudeau, Arlyn E. Andrews, Zichong Chen, and Scot M. Miller
Geosci. Model Dev., 14, 4683–4696, https://doi.org/10.5194/gmd-14-4683-2021, https://doi.org/10.5194/gmd-14-4683-2021, 2021
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Observations of greenhouse gases have become far more numerous in recent years due to new satellite observations. The sheer size of these datasets makes it challenging to incorporate these data into statistical models and use these data to estimate greenhouse gas sources and sinks. In this paper, we develop an approach to reduce the size of these datasets while preserving the most information possible. We subsequently test this approach using satellite observations of carbon dioxide.
Claudio A. Belis, Guido Pirovano, Maria Gabriella Villani, Giuseppe Calori, Nicola Pepe, and Jean Philippe Putaud
Geosci. Model Dev., 14, 4731–4750, https://doi.org/10.5194/gmd-14-4731-2021, https://doi.org/10.5194/gmd-14-4731-2021, 2021
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The study presents an in-depth analysis of the implications that using different CTM source apportionment approaches (tagged species and brute force) have for the source allocation of secondary inorganic aerosol, an important component of PM10 and PM2.5. A set of runs combining different emission levels and models was carried out, aiming to describe the situations in which strong non-linearity may lead the two approaches to deliver different results and when they are expected to be comparable.
Luolin Wu, Jian Hang, Xuemei Wang, Min Shao, and Cheng Gong
Geosci. Model Dev., 14, 4655–4681, https://doi.org/10.5194/gmd-14-4655-2021, https://doi.org/10.5194/gmd-14-4655-2021, 2021
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In order to investigate street-scale flow and air quality, this study has developed APFoam 1.0 to examine the reactive pollutant formation and dispersion in the urban area. The model has been validated and shows good agreement with wind tunnel experimental data. Model sensitivity cases reveal that vehicle emissions, background concentrations, and wind conditions are the key factors affecting the photochemical reaction process.
Lin Huang, Song Liu, Zeyuan Yang, Jia Xing, Jia Zhang, Jiang Bian, Siwei Li, Shovan Kumar Sahu, Shuxiao Wang, and Tie-Yan Liu
Geosci. Model Dev., 14, 4641–4654, https://doi.org/10.5194/gmd-14-4641-2021, https://doi.org/10.5194/gmd-14-4641-2021, 2021
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Accurate estimation of emissions is a prerequisite for effectively controlling air pollution, but current methods lack either sufficient data or a representation of nonlinearity. Here, we proposed a novel deep learning method to model the dual relationship between emissions and pollutant concentrations. Emissions can be updated by back-propagating the gradient of the loss function measuring the deviation between simulations and observations, resulting in better model performance.
Christian Zeman, Nils P. Wedi, Peter D. Dueben, Nikolina Ban, and Christoph Schär
Geosci. Model Dev., 14, 4617–4639, https://doi.org/10.5194/gmd-14-4617-2021, https://doi.org/10.5194/gmd-14-4617-2021, 2021
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Kilometer-scale atmospheric models allow us to partially resolve thunderstorms and thus improve their representation. We present an intercomparison between two distinct atmospheric models for 2 summer days with heavy thunderstorms over Europe. We show the dependence of precipitation and vertical wind speed on spatial and temporal resolution and also discuss the possible influence of the system of equations, numerical methods, and diffusion in the models.
Edward C. Chan and Timothy M. Butler
Geosci. Model Dev., 14, 4555–4572, https://doi.org/10.5194/gmd-14-4555-2021, https://doi.org/10.5194/gmd-14-4555-2021, 2021
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A large-eddy simulation based chemical transport model is implemented for an idealized street canyon. The dynamics of the model are evaluated using stationary measurements. A transient model run is also conducted over a 24 h period, where variations of pollutant concentrations indicate dependence on emissions, background concentrations, and solar state. Comparison stationary model runs show changes in flow structure concentrations.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Michal Belda, Jaroslav Resler, Jan Geletič, Pavel Krč, Björn Maronga, Matthias Sühring, Mona Kurppa, Farah Kanani-Sühring, Vladimír Fuka, Kryštof Eben, Nina Benešová, and Mikko Auvinen
Geosci. Model Dev., 14, 4443–4464, https://doi.org/10.5194/gmd-14-4443-2021, https://doi.org/10.5194/gmd-14-4443-2021, 2021
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The analysis summarizes how sensitive the modelling of urban environment is to changes in physical parameters describing the city (e.g. reflectivity of surfaces) and to several heat island mitigation scenarios in a city quarter in Prague, Czech Republic. We used the large-eddy simulation modelling system PALM 6.0. Surface parameters connected to radiation show the highest sensitivity in this configuration. For heat island mitigation, urban vegetation is shown to be the most effective measure.
Ying Wei, Xueshun Chen, Huansheng Chen, Yele Sun, Wenyi Yang, Huiyun Du, Qizhong Wu, Dan Chen, Xiujuan Zhao, Jie Li, and Zifa Wang
Geosci. Model Dev., 14, 4411–4428, https://doi.org/10.5194/gmd-14-4411-2021, https://doi.org/10.5194/gmd-14-4411-2021, 2021
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The sub-grid particle formation (SGPF) in plumes plays an important role in air pollution and climate. We coupled an SGPF scheme to a chemical transport model with an aerosol microphysics module and applied it to investigate the SGPF impact over China. The scheme clearly improved the model performance in simulating aerosol components and particle number at typical sites influenced by point sources. The results indicate the significant effects of SGPF on aerosol particles in industrial areas.
Eduardo Rossi and Costanza Bonadonna
Geosci. Model Dev., 14, 4379–4400, https://doi.org/10.5194/gmd-14-4379-2021, https://doi.org/10.5194/gmd-14-4379-2021, 2021
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SCARLET-1.0 is a MATLAB package that creates virtual aggregates starting from a population of irregular shapes. Shapes are described in terms of the Standard Triangulation Language (STL) format, and this allows importing a great variety of shapes, such as from 3D scanning. The package produces a new STL file as an output and different analytical information about the packing, such as the porosity. It has been specifically designed for use in volcanology and scientific education.
Chun-Hsu Su, Nathan Eizenberg, Dörte Jakob, Paul Fox-Hughes, Peter Steinle, Christopher J. White, and Charmaine Franklin
Geosci. Model Dev., 14, 4357–4378, https://doi.org/10.5194/gmd-14-4357-2021, https://doi.org/10.5194/gmd-14-4357-2021, 2021
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The Bureau of Meteorology Atmospheric Regional Reanalysis for Australia (BARRA) has produced a very high-resolution reconstruction of Australian historical weather from 1990 to 2018. This paper demonstrates the added weather and climate information to supplement coarse- or moderate-resolution regional and global reanalyses. The new climate data can allow greater understanding of past weather, including extreme events, at very local kilometre scales.
Jun Meng, Randall V. Martin, Paul Ginoux, Melanie Hammer, Melissa P. Sulprizio, David A. Ridley, and Aaron van Donkelaar
Geosci. Model Dev., 14, 4249–4260, https://doi.org/10.5194/gmd-14-4249-2021, https://doi.org/10.5194/gmd-14-4249-2021, 2021
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Dust emissions in models, for example, GEOS-Chem, have a strong nonlinear dependence on meteorology, which means dust emission strengths calculated from different resolution meteorological fields are different. Offline high-resolution dust emissions with an optimized global dust strength, presented in this work, can be implemented into GEOS-Chem as offline emission inventory so that it could promote model development by harmonizing dust emissions across simulations of different resolutions.
Simon Rosanka, Rolf Sander, Andreas Wahner, and Domenico Taraborrelli
Geosci. Model Dev., 14, 4103–4115, https://doi.org/10.5194/gmd-14-4103-2021, https://doi.org/10.5194/gmd-14-4103-2021, 2021
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The Jülich Aqueous-phase Mechanism of Organic Chemistry (JAMOC) is developed and implemented into the Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA). JAMOC is an explicit in-cloud oxidation scheme for oxygenated volatile organic compounds (OVOCs), which is suitable for global model applications. Within a box-model study, we show that JAMOC yields reduced gas-phase concentrations of most OVOCs and oxidants, except for nitrogen oxides.
Matthieu Pommier
Geosci. Model Dev., 14, 4143–4158, https://doi.org/10.5194/gmd-14-4143-2021, https://doi.org/10.5194/gmd-14-4143-2021, 2021
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Within the Copernicus Atmosphere Monitoring Service (CAMS), a forecasting system calculating the city source contribution for the surface urban background PM10 in European cities has been developed. The system uses the EMEP model and this paper presents the product by focusing on an event which occurred from 1 to 9 December 2016.
Erik Johansson, Abhay Devasthale, Michael Tjernström, Annica M. L. Ekman, Klaus Wyser, and Tristan L'Ecuyer
Geosci. Model Dev., 14, 4087–4101, https://doi.org/10.5194/gmd-14-4087-2021, https://doi.org/10.5194/gmd-14-4087-2021, 2021
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Understanding the coupling of clouds to large-scale circulation is a grand challenge for the climate community. Cloud radiative heating (CRH) is a key parameter in this coupling and is therefore essential to model realistically. We, therefore, evaluate a climate model against satellite observations. Our findings indicate good agreement in the seasonal pattern of CRH even if the magnitude differs. We also find that increasing the horizontal resolution in the model has little effect on the CRH.
Xiaoyang Chen, Yang Zhang, Kai Wang, Daniel Tong, Pius Lee, Youhua Tang, Jianping Huang, Patrick C. Campbell, Jeff Mcqueen, Havala O. T. Pye, Benjamin N. Murphy, and Daiwen Kang
Geosci. Model Dev., 14, 3969–3993, https://doi.org/10.5194/gmd-14-3969-2021, https://doi.org/10.5194/gmd-14-3969-2021, 2021
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The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality forecasts. To support the development of the next-generation NAQFC, we evaluate a prototype of GFSv15-CMAQv5.0.2. The performance and the potential improvements for the system are discussed. This study can provide a scientific basis for further development of NAQFC and help it to provide more accurate air quality forecasts to the public over the contiguous United States.
Dawei Li, Yudi Liu, and Chaohui Chen
Geosci. Model Dev., 14, 4019–4034, https://doi.org/10.5194/gmd-14-4019-2021, https://doi.org/10.5194/gmd-14-4019-2021, 2021
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In the daily weather forecast business, numerical weather prediction is mainly used to forecast precipitation, but its performance for nowcasting tasks within 0–2 h is very poor. Hence, we hope to use machine learning to improve the accuracy and resolution of quantitative precipitation nowcasting (QPN) tasks. Previous works focused on the extrapolation of radar echo without using abundant meteorological data. Therefore, we designed a model using three kinds of data for QPN in eastern china.
Mark R. Muetzelfeldt, Robert S. Plant, Peter A. Clark, Alison J. Stirling, and Steven J. Woolnough
Geosci. Model Dev., 14, 4035–4049, https://doi.org/10.5194/gmd-14-4035-2021, https://doi.org/10.5194/gmd-14-4035-2021, 2021
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Wind shear causes organized convection in the tropics, producing, e.g., squall lines. We have developed a procedure for producing a climatology of sheared wind profiles in a climate model and demonstrated that the profiles are linked with organized convection, both in terms of their structure and their spatio-temporal distribution. The procedure could be used to diagnose organization of convection in a climate model, which could lead to improvements in the model's representation of convection.
Carlos Román-Cascón, Marie Lothon, Fabienne Lohou, Oscar Hartogensis, Jordi Vila-Guerau de Arellano, David Pino, Carlos Yagüe, and Eric R. Pardyjak
Geosci. Model Dev., 14, 3939–3967, https://doi.org/10.5194/gmd-14-3939-2021, https://doi.org/10.5194/gmd-14-3939-2021, 2021
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The type of vegetation (or land cover) and its status influence the heat and water transfers between the surface and the air, affecting the processes that develop in the atmosphere at different (but connected) spatiotemporal scales. In this work, we investigate how these transfers are affected by the way the surface is represented in a widely used weather model. The results encourage including realistic high-resolution and updated land cover databases in models to improve their predictions.
Phuc T. M. Ha, Ryoki Matsuda, Yugo Kanaya, Fumikazu Taketani, and Kengo Sudo
Geosci. Model Dev., 14, 3813–3841, https://doi.org/10.5194/gmd-14-3813-2021, https://doi.org/10.5194/gmd-14-3813-2021, 2021
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Policies to mitigate air pollution require an understanding of tropospheric oxidizing capacity, which is controlled by mechanisms including heterogeneous processes on aerosols and clouds. This study uses a chemistry–climate model CHASER (MIROC) to explore the heterogeneous effects in the troposphere for -2.96 % O3, -2.19 % NOx, +3.28 % CO, and +5.91 % CH4 lifetime. Besides, these processes affect polluted areas and remote areas and can bring challenges to pollution reduction efforts.
Robin Stoffer, Caspar M. van Leeuwen, Damian Podareanu, Valeriu Codreanu, Menno A. Veerman, Martin Janssens, Oscar K. Hartogensis, and Chiel C. van Heerwaarden
Geosci. Model Dev., 14, 3769–3788, https://doi.org/10.5194/gmd-14-3769-2021, https://doi.org/10.5194/gmd-14-3769-2021, 2021
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Turbulent flows are often simulated with the large-eddy simulation (LES) technique, which requires subgrid models to account for the smallest scales. Current subgrid models often require strong simplifying assumptions. We therefore developed a subgrid model based on artificial neural networks, which requires fewer assumptions. Our data-driven SGS model showed high potential in accurately representing the smallest scales but still introduced instability when incorporated into an actual LES.
Xu Feng, Haipeng Lin, Tzung-May Fu, Melissa P. Sulprizio, Jiawei Zhuang, Daniel J. Jacob, Heng Tian, Yaping Ma, Lijuan Zhang, Xiaolin Wang, Qi Chen, and Zhiwei Han
Geosci. Model Dev., 14, 3741–3768, https://doi.org/10.5194/gmd-14-3741-2021, https://doi.org/10.5194/gmd-14-3741-2021, 2021
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WRF-GC is an online coupling of the WRF meteorological model and GEOS-Chem chemical transport model for regional atmospheric chemistry and air quality modeling. In WRF-GC v2.0, we implemented the aerosol–radiation interactions and aerosol–cloud interactions, as well as the capability to nest multiple domains for high-resolution simulations based on the modular framework of WRF-GC v1.0. This allows the GEOS-Chem users to investigate the meteorology–atmospheric chemistry interactions.
Robin D. Lamboll, Chris D. Jones, Ragnhild B. Skeie, Stephanie Fiedler, Bjørn H. Samset, Nathan P. Gillett, Joeri Rogelj, and Piers M. Forster
Geosci. Model Dev., 14, 3683–3695, https://doi.org/10.5194/gmd-14-3683-2021, https://doi.org/10.5194/gmd-14-3683-2021, 2021
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Lockdowns to avoid the spread of COVID-19 have created an unprecedented reduction in human emissions. We can estimate the changes in emissions at a country level, but to make predictions about how this will affect our climate, we need more precise information about where the emissions happen. Here we combine older estimates of where emissions normally occur with very recent estimates of sector activity levels to enable different groups to make simulations of the climatic effects of lockdown.
Nina Črnivec and Bernhard Mayer
Geosci. Model Dev., 14, 3663–3682, https://doi.org/10.5194/gmd-14-3663-2021, https://doi.org/10.5194/gmd-14-3663-2021, 2021
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This study aims to advance the cloud–radiation interplay treatment in global weather and climate prediction, focusing on cloud horizontal inhomogeneity misrepresentation. We explore the potential of the Tripleclouds method for diverse cloud types, namely the stratocumulus, cirrus and cumulonimbus. The validity of global cloud variability estimate with various condensate distribution assumptions is assessed. Optimizations for overcast and extremely heterogeneous cloudiness are further endorsed.
Dien Wu, John C. Lin, Henrique F. Duarte, Vineet Yadav, Nicholas C. Parazoo, Tomohiro Oda, and Eric A. Kort
Geosci. Model Dev., 14, 3633–3661, https://doi.org/10.5194/gmd-14-3633-2021, https://doi.org/10.5194/gmd-14-3633-2021, 2021
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A model (SMUrF) is presented that estimates biogenic CO2 fluxes over cities around the globe to separate out biogenic fluxes from anthropogenic emissions. The model leverages satellite-based solar-induced fluorescence data and a machine-learning technique. We evaluate the biogenic fluxes against flux observations and show contrasts between biogenic and anthropogenic fluxes over cities, revealing urban–rural flux gradients, diurnal cycles, and the resulting imprints on atmospheric-column CO2.
Sarah Sparrow, Andrew Bowery, Glenn D. Carver, Marcus O. Köhler, Pirkka Ollinaho, Florian Pappenberger, David Wallom, and Antje Weisheimer
Geosci. Model Dev., 14, 3473–3486, https://doi.org/10.5194/gmd-14-3473-2021, https://doi.org/10.5194/gmd-14-3473-2021, 2021
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This paper describes how the research version of the European Centre for Medium-Range Weather Forecasts’ Integrated Forecast System is combined with climateprediction.net’s public volunteer computing resource to develop OpenIFS@home. Thousands of volunteer personal computers simulated slightly different realizations of Tropical Cyclone Karl to demonstrate the performance of the large-ensemble forecast. OpenIFS@Home offers researchers a new tool to study weather forecasts and related questions.
Guillaume Monteil and Marko Scholze
Geosci. Model Dev., 14, 3383–3406, https://doi.org/10.5194/gmd-14-3383-2021, https://doi.org/10.5194/gmd-14-3383-2021, 2021
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LUMIA is a Python library for atmospheric inversions, originally developed at Lund University to perform regional atmospheric CO2 inversions. The inversions rely on coupling the regional transport model FLEXPART and the global transport model TM5. The paper presents the modeling setup and some first results, and it introduces the LUMIA Python package as a toolbox for inversions beyond the use case presented in the paper.
Benjamin N. Murphy, Christopher G. Nolte, Fahim Sidi, Jesse O. Bash, K. Wyat Appel, Carey Jang, Daiwen Kang, James Kelly, Rohit Mathur, Sergey Napelenok, George Pouliot, and Havala O. T. Pye
Geosci. Model Dev., 14, 3407–3420, https://doi.org/10.5194/gmd-14-3407-2021, https://doi.org/10.5194/gmd-14-3407-2021, 2021
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The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality (CMAQ) model have been improved to better support users and developers. The new features accommodate emissions perturbation studies that are typical in atmospheric research and output a wealth of metadata for each model run so assumptions can be verified and documented. The new approach dramatically enhances the transparency and functionality of this critical aspect of atmospheric modeling.
Tobias Gronemeier, Kerstin Surm, Frank Harms, Bernd Leitl, Björn Maronga, and Siegfried Raasch
Geosci. Model Dev., 14, 3317–3333, https://doi.org/10.5194/gmd-14-3317-2021, https://doi.org/10.5194/gmd-14-3317-2021, 2021
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We demonstrate the capability of the PALM model system version 6.0 to simulate urban boundary layers. The studied situation includes a real-world building setup of the HafenCity area in Hamburg, Germany. We evaluate the simulation results against wind-tunnel measurements utilizing PALM's virtual measurement module. The comparison reveals an overall high agreement between simulation results and wind-tunnel measurements including mean wind speed and direction as well as turbulence statistics.
Sara M. Blichner, Moa K. Sporre, Risto Makkonen, and Terje K. Berntsen
Geosci. Model Dev., 14, 3335–3359, https://doi.org/10.5194/gmd-14-3335-2021, https://doi.org/10.5194/gmd-14-3335-2021, 2021
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Aerosol–cloud interactions are the largest contributor to climate forcing uncertainty. In this study we combine two common approaches to aerosol representation in global models: a sectional scheme, which is closer to first principals, for the smallest particles forming in the atmosphere and a log-modal scheme, which is faster, for the larger particles. With this approach, we improve the aerosol representation compared to observations, while only increasing the computational cost by 15 %.
Timothy Glotfelty, Diana Ramírez-Mejía, Jared Bowden, Adrian Ghilardi, and J. Jason West
Geosci. Model Dev., 14, 3215–3249, https://doi.org/10.5194/gmd-14-3215-2021, https://doi.org/10.5194/gmd-14-3215-2021, 2021
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Land use and land cover change is a major contributor to climate change in Africa. Here we document deficiencies in how a weather model represents the land surface of Africa and how we modify a common land surface model to overcome these deficiencies. Our tests reveal that the default weather model does not accurately predict and transition the properties of different African biomes and growing cycles. This paper demonstrates that our modified model addresses these limitations.
Mario Eduardo Gavidia-Calderón, Sergio Ibarra-Espinosa, Youngseob Kim, Yang Zhang, and Maria de Fatima Andrade
Geosci. Model Dev., 14, 3251–3268, https://doi.org/10.5194/gmd-14-3251-2021, https://doi.org/10.5194/gmd-14-3251-2021, 2021
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The MUNICH model was used to calculate pollutant concentrations inside the streets of São Paulo. The VEIN emission model provided the vehicular emissions and the coordinates of the streets. We used information from an air quality station to account for pollutant concentrations over the street rooftops. Results showed that when emissions are calibrated, MUNICH satisfied the performance criteria. MUNICH can be used to evaluate the impact of traffic-related air pollution on public health.
Xiaoli G. Larsén and Jana Fischereit
Geosci. Model Dev., 14, 3141–3158, https://doi.org/10.5194/gmd-14-3141-2021, https://doi.org/10.5194/gmd-14-3141-2021, 2021
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For the first time, turbulent kinetic energy (TKE) calculated from the explicit wake parameterization (EWP) in WRF is examined using high-frequency measurements over a wind farm and compared with that calculated using the Fitch et al. (2012) scheme. We examined the effect of farm-induced TKE advection in connection with the Fitch scheme. Through a case study with a low-level jet (LLJ), we analyzed the key features of LLJs and raised the issue of interaction between wind farms and LLJs.
Pavel Krč, Jaroslav Resler, Matthias Sühring, Sebastian Schubert, Mohamed H. Salim, and Vladimír Fuka
Geosci. Model Dev., 14, 3095–3120, https://doi.org/10.5194/gmd-14-3095-2021, https://doi.org/10.5194/gmd-14-3095-2021, 2021
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The adverse effects of an urban environment, e.g. heat stress and air pollution, pose a risk to health and well-being. Precise modelling of the urban climate is crucial to mitigate these effects. Conventional atmospheric models are inadequate for modelling the complex structures of the urban environment; in particular, they lack a 3-D model of radiation and its interaction with surfaces and the plant canopy. The new RTM simulates these processes within the PALM-4U urban climate model.
Tao Zheng, Sha Feng, Kenneth J. Davis, Sandip Pal, and Josep-Anton Morguí
Geosci. Model Dev., 14, 3037–3066, https://doi.org/10.5194/gmd-14-3037-2021, https://doi.org/10.5194/gmd-14-3037-2021, 2021
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Carbon dioxide is the most important greenhouse gas. We develop the numerical model that represents carbon dioxide transport in the atmosphere. This model development is based on the MPAS model, which has a variable-resolution capability. The purpose of developing carbon dioxide transport in MPAS is to allow for high-resolution transport model simulation that is not limited by the lateral boundaries. It will also form the base for a future development of MPAS-based carbon inversion system.
Cited articles
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, 1989.
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.
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.
Andrejczuk, M., Gadian, A., and Blyth, A.: Stratocumulus over SouthEast Pacific: Idealized 2D simulations with the Lagrangian Cloud Model, ArXiv e-prints, 1211.0193v1 [physics.ao-ph], 2012.
Arabas, S. and Shima, S.-I.: Large-Eddy Simulations of Trade Wind Cumuli Using Particle-Based Microphysics with Monte Carlo Coalescence, J. Atmos. Sci., 70, 2768–2777, https://doi.org/10.1175/JAS-D-12-0295.1, 2013.
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.
Ayala, O., Rosa, B., and Wang, L.-P.: Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 2. Theory and parameterization, New Journal of Physics, 10, 075016, https://doi.org/10.1088/1367-2630/10/7/075016, 2008.
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.
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.
Berry, E. X. and Reinhardt, R. L.: An Analysis of Cloud Drop Growth by Collection Part II. Single Initial Distributions, J. Atmos. Sci., 31, 1825–1831, https://doi.org/10.1175/1520-0469(1974)031<1825:AAOCDG>2.0.CO;2, 1974.
Bott, A.: A Flux Method for the Numerical Solution of the Stochastic Collection Equation, J. Atmos. Sci., 55, 2284–2293, https://doi.org/10.1175/1520-0469(1998)055<2284:AFMFTN>2.0.CO;2, 1998.
Chen, S., Bartello, P., Yau, M. K., Vaillancourt, P. A., and Zwijsen, K.: Cloud Droplet Collisions in Turbulent Environment: Collision Statistics and Parameterization, J. Atmos. Sci., 73, 621–636, https://doi.org/10.1175/JAS-D-15-0203.1, 2016.
Connolly, P. J., Emersic, C., and Field, P. R.: A laboratory investigation into the aggregation efficiency of small ice crystals, Atmos. Chem. Phys., 12, 2055–2076, https://doi.org/10.5194/acp-12-2055-2012, 2012.
DeVille, R., Riemer, N., and West, M.: Weighted Flow Algorithms (WFA) for stochastic particle coagulation, J. Comput. Phys., 230, 8427–8451, https://doi.org/10.1016/j.jcp.2011.07.027, 2011.
Devroye, L.: Non-Uniform Random Variate Generation, Springer-Verlag, New York, https://doi.org/10.1007/978-1-4613-8643-8, 1986.
Estivill-Castro, V. and Wood, D.: A Survey of Adaptive Sorting Algorithms, ACM Comput. Surv., 24, 441–476, https://doi.org/10.1145/146370.146381, 1992.
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.
Gillespie, D. T.: An Exact Method for Numerically Simulating the Stochastic Coalescence Process in a Cloud, J. Atmos. Sci., 32, 1977–1989, https://doi.org/10.1175/1520-0469(1975)032<1977:AEMFNS>2.0.CO;2, 1975.
Golovin, A. M.: The solution of the coagulation equation for cloud droplets in a rising air current, Bull. Acad. Sci. USSR, Geophys. Ser., 5, 783–791, 1963.
Grabowski, W. W. and Wang, L.-P.: Growth of Cloud Droplets in a Turbulent Environment, Annual Rev. Fluid Mech., 45, 293–324, https://doi.org/10.1146/annurev-fluid-011212-140750, 2013.
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.
Heymsfield, A. and Westbrook, C.: Advances in the estimation of ice particle fall speeds using laboratory and field measurements, J. Atmos. Sci., 67, 2469–2482, 2010.
Hoffmann, F.: The Effect of Spurious Cloud Edge Supersaturations in Lagrangian Cloud Models: An Analytical and Numerical Study, Mon. Weather Rev., 144, 107–118, https://doi.org/10.1175/MWR-D-15-0234.1, 2016.
Hoffmann, F., Raasch, S., and Noh, Y.: Entrainment of aerosols and their activation in a shallow cumulus cloud studied with a coupled LCM-LES approach, Atmos. Res., 156, 43–57, https://doi.org/10.1016/j.atmosres.2014.12.008, 2015.
Kessler, E.: Models of microphysical parameters and processes, Meteorol. Monogr., 10, 26–31, 1969.
Khain, A., Ovtchinnikov, M., Pinsky, M., Pokrovsky, A., and Krugliak, H.: Notes on the state-of-the-art numerical modeling of cloud microphysics, Atmos. Res., 55, 159–224, 2000.
Khairoutdinov, M. and Kogan, Y.: A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus, Mon. Weather Rev., 128, 229–243, 2000.
Kolodko, A. and Sabelfeld, K.: Stochastic particle methods for Smoluchowski coagulation equation: Variance reduction and error estimations, Monte Carlo Methods and Applications, 9, 315–339, https://doi.org/10.1163/156939603322601950, 2003.
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.
L'Ecuyer, P. and Simard, R.: TestU01: A C Library for Empirical Testing of Random Number Generators, ACM Trans. Math. Softw., 33, https://doi.org/10.1145/1268776.1268777, 2007.
Lee, J., Noh, Y., Raasch, S., Riechelmann, T., and Wang, L.-P.: Investigation of droplet dynamics in a convective cloud using a Lagrangian cloud model, Meteorol. Atmos. Phys., 124, 1–21, https://doi.org/10.1007/s00703-014-0311-y, 2014.
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.
Maisels, A., Einar Kruis, F., and Fissan, H.: Direct simulation Monte Carlo for simultaneous nucleation, coagulation, and surface growth in dispersed systems, Chem. Eng. Sci., 59, 2231–2239, https://doi.org/10.1016/j.ces.2004.02.015, 2004.
Maronga, B., Gryschka, M., Heinze, R., Hoffmann, F., Kanani-Sühring, F., Keck, M., Ketelsen, K., Letzel, M. O., Sühring, M., and Raasch, S.: The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives, Geosci. Model Dev., 8, 2515–2551, https://doi.org/10.5194/gmd-8-2515-2015, 2015.
Matsumoto, M. and Nishimura, T.: Mersenne Twister: a 623-dimensionally equidistributed uniform pseudo-random number generator, ACM Transactions on Modeling and Computer Simulation, 8, 3–30, 1998.
Mitchell, D.: Use of mass- and area-dimensional power laws for determining precipitation particle terminal velocities, J. Atmos. Sci., 53, 1710–1723, 1996.
Naumann, A. K. and Seifert, A.: A Lagrangian drop model to study warm rain microphysical processes in shallow cumulus, J. Adv. Model. Earth Syst., 7, 1136–1154, 2015.
Naumann, A. K. and Seifert, A.: Recirculation and growth of raindrops in simulated shallow cumulus, Journal of Advances in Modeling Earth Systems, 8, 520–537, https://doi.org/10.1002/2016MS000631, 2016.
Paoli, R., Hélie, J., and Poinsot, T.: Contrail formation in aircraft wakes, J. Fluid Mech., 502, 361–373, 2004.
Paoli, R., Nybelen, L., Picot, J., and Cariolle, D.: Effects of jet/vortex interaction on contrail formation in supersaturated conditions, Phys. Fluids, 25, 1–28, https://doi.org/10.1063/1.4807063, 2013.
Rade, L. and Westergren, B.: Springers mathematische Formeln: Taschenbuch für Ingenieure, Naturwissenschaftler, Informatiker, Wirtschaftswissenschaftler, Springer Berlin Heidelberg, https://doi.org/10.1007/978-3-642-57239-5, 2000.
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 Journal of Physics, 14, 065008, https://doi.org/10.1088/1367-2630/14/6/065008, 2012.
Riemer, N., West, M., Zaveri, R. A., and Easter, R. C.: Simulating the evolution of soot mixing state with a particle-resolved aerosol model, J. Geophys. Res., 114, d09202, https://doi.org/10.1029/2008JD011073, 2009.
Schmitt, C. G. and Heymsfield, A. J.: The Dimensional Characteristics of Ice Crystal Aggregates from Fractal Geometry, J. Atmos. Sci., 67, 1605–1616, https://doi.org/10.1175/2009JAS3187.1, 2010.
Scott, W. T.: Analytic Studies of Cloud Droplet Coalescence I, J. Atmos. Sci., 25, 54–65, https://doi.org/10.1175/1520-0469(1968)025<0054:ASOCDC>2.0.CO;2, 1968.
Seifert, A. and Beheng, K. D.: A double-moment parameterization for simulating autoconversion, accretion and selfcollection, Atmos. Res., 59, 265–281, 2001.
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. Roy. Meteorol. Soc., 135, 1307–1320, 2009.
Shirgaonkar, A. and Lele, S.: Large Eddy Simulation of Early Stage Contrails: Effect of Atmospheric Properties, 44 th AIAA Aerospace Sciences Meeting and Exhibit, 0, 1–13, 2006.
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, 2002.
Sölch, I. and Kärcher, B.: A large-eddy model for cirrus clouds with explicit aerosol and ice microphysics and Lagrangian ice particle tracking, Q. J. Roy. Meteorol. Soc., 136, 2074–2093, 2010.
Sölch, I. and Kärcher, B.: Process-oriented large-eddy simulations of a midlatitude cirrus cloud system based on observations, Q. J. Roy. Meteorol. Soc., 137, 374–393, 2011.
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.
Unterstrasser, S.: Large eddy simulation study of contrail microphysics and geometry during the vortex phase and consequences on contrail-to-cirrus transition, J. Geophys. Res., 119, 7537–7555, https://doi.org/10.1002/2013JD021418, 2014.
Unterstrasser, S. and Görsch, N.: Aircraft-type dependency of contrail evolution, J. Geophys. Res., 119, 14015–14027, https://doi.org/10.1002/2014JD022642, 2014.
Unterstrasser, S. and Sölch, I.: Optimisation of the simulation particle number in a Lagrangian ice microphysical model, Geosci. Model Dev., 7, 695–709, https://doi.org/10.5194/gmd-7-695-2014, 2014.
Unterstrasser, S., Gierens, K., Sölch, I., and Wirth, M.: Numerical simulations of homogeneously nucleated natural cirrus and contrail-cirrus. Part 2: Interaction on local scale, Meteorol. Z., https://doi.org/10.1127/metz/2016/0780, in press, 2016.
Wacker, U. and Seifert, A.: Evolution of rain water profiles resulting from pure sedimentation: Spectral vs. parameterized description, Atmos. Res., 58, 19–39, 2001.
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, 2006.
Wang, L.-P., Xue, Y., and Grabowski, W. W.: A bin integral method for solving the kinetic collection equation, J. Comput. Phys., 226, 59–88, 2007.
Xue, H., Feingold, G., and Stevens, B.: Aerosol effects on clouds, precipitation, and the organization of shallow cumulus convection, J. Atmos. Sci., 65, 392–406, 2008.
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.
In the last decade, several Lagrangian microphysical models (LCMs) have been developed which use...
