Articles | Volume 8, issue 6
Model description paper 22 Jun 2015
Model description paper | 22 Jun 2015
simpleGAMMA v1.0 – a reduced model of secondary organic aerosol formation in the aqueous aerosol phase (aaSOA)
J. L. Woo and V. F. McNeill
No articles found.
E. A. Marais, D. J. Jacob, J. L. Jimenez, P. Campuzano-Jost, D. A. Day, W. Hu, J. Krechmer, L. Zhu, P. S. Kim, C. C. Miller, J. A. Fisher, K. Travis, K. Yu, T. F. Hanisco, G. M. Wolfe, H. L. Arkinson, H. O. T. Pye, K. D. Froyd, J. Liao, and V. F. McNeill
Atmos. Chem. Phys., 16, 1603–1618,Short summary
Isoprene secondary organic aerosol (SOA) is a dominant aerosol component in the southeast US, but models routinely underestimate isoprene SOA with traditional schemes based on chamber studies operated under conditions not representative of isoprene-emitting forests. We develop a new irreversible uptake mechanism to reproduce isoprene SOA yields (3.3 %) and composition, and find a factor of 2 co-benefit of SO2 emission controls on reducing sulfate and organic aerosol in the southeast US.
S. H. Budisulistiorini, X. Li, S. T. Bairai, J. Renfro, Y. Liu, Y. J. Liu, K. A. McKinney, S. T. Martin, V. F. McNeill, H. O. T. Pye, A. Nenes, M. E. Neff, E. A. Stone, S. Mueller, C. Knote, S. L. Shaw, Z. Zhang, A. Gold, and J. D. Surratt
Atmos. Chem. Phys., 15, 8871–8888,Short summary
Isoprene epoxydiols (IEPOX) are major gas-phase products from the atmospheric oxidation of isoprene that yield secondary organic aerosol (SOA) by reactive uptake onto acidic sulfate aerosol. We report a substantial contribution of IEPOX-derived SOA to the total fine aerosol collected during summer. IEPOX-derived SOA measured by online and offline mass spectrometry techniques is correlated with acidic sulfate aerosol, demonstrating the critical role of anthropogenic emissions in its formation.
M. A. Upshur, B. F. Strick, V. F. McNeill, R. J. Thomson, and F. M. Geiger
Atmos. Chem. Phys., 14, 10731–10740,
G. Drozd, J. Woo, S. A. K. Häkkinen, A. Nenes, and V. F. McNeill
Atmos. Chem. Phys., 14, 5205–5215,
A. N. Schwier, G. A. Viglione, Z. Li, and V. Faye McNeill
Atmos. Chem. Phys., 13, 10721–10732,
G. T. Drozd, J. L. Woo, and V. F. McNeill
Atmos. Chem. Phys., 13, 8255–8263,
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This paper presents an evaluation of the E3SM model against NEXRAD radar observations for the warm seasons during 2014–2016. The COSP forward simulator package is implemented in the model to generate radar reflectivity, and the NEXRAD observations are coarsened to the model resolution for comparison. The model severely underestimates the reflectivity above 4 km. Sensitivity tests on the parameters from cumulus parameterization and cloud microphysics do not improve this model bias.
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Felix Kleinert, Lukas H. Leufen, and Martin G. Schultz
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Adrien Napoly, Aaron Boone, and Théo Welfringer
Geosci. Model Dev., 13, 6523–6545,Short summary
Accurate modeling of snow impact on surface energy and mass fluxes is required from land surface models. This new version of the SURFEX model improves the representation of the snowpack. In particular, it prevents its ablation from occurring too early in the season, which also leads to better soil temperatures and energy fluxes toward the atmosphere. This was made possible with a more explicit and distinct representation of each layer that constitutes the surface (soil, snow, and vegetation).
Robin J. Hogan and Marco Matricardi
Geosci. Model Dev., 13, 6501–6521,Short summary
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David Simpson, Robert Bergström, Alan Briolat, Hannah Imhof, John Johansson, Michael Priestley, and Alvaro Valdebenito
Geosci. Model Dev., 13, 6447–6465,Short summary
This paper outlines the structure and usage of the GenChem system, which includes a chemical pre-processor (GenChem.py) and a simple box model (boxChem). GenChem provides scripts and input files for converting chemical equations into differential form for use in atmospheric chemical transport models (CTMs) and/or the boxChem system. Although GenChem is primarily intended for users of the EMEP MSC-W CTM and related systems, boxChem can be run as a stand-alone chemical solver.
Zhiqiang Li, Bingcheng Wan, Yulun Zhou, and Hokit Wong
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Our results provide evidence of the effects of incoming land surface data quality on the accuracy of high-resolution urban climate simulations and emphasize the importance of the incoming data quality control.
Yihui Zhou, Yi Zhang, Jian Li, Rucong Yu, and Zhuang Liu
Geosci. Model Dev., 13, 6325–6348,Short summary
This paper explores the configuration of a global atmospheric model (global-to-regional integrated forecast system-atmosphere; GRIST-A) with various multiresolution grids. The model performance is evaluated from dry dynamics to simple physics and full physics. The model is able to resolve the fine-scale structures in the grid-refinement region, and the adverse impact due to the mesh transition and the coarse-resolution area can be controlled well.
Bruce Rolstad Denby, Michael Gauss, Peter Wind, Qing Mu, Eivind Grøtting Wærsted, Hilde Fagerli, Alvaro Valdebenito, and Heiko Klein
Geosci. Model Dev., 13, 6303–6323,Short summary
Air pollution is both a local and a global problem. Since measurements cannot be made everywhere, mathematical models are used to calculate air quality over cities or countries. Modelling over countries limits the level of detail of the models. For countries, the level of detail is only a few kilometres, so air quality at kerb sides is not properly represented. The uEMEP model is used together with the regional air quality model EMEP MSC-W to model details down to kerb side for all of Norway.
Yanfei Liang, Zengliang Zang, Dong Liu, Peng Yan, Yiwen Hu, Yan Zhou, and Wei You
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Ebrahim Eslami, Yunsoo Choi, Yannic Lops, Alqamah Sayeed, and Ahmed Khan Salman
Geosci. Model Dev., 13, 6237–6251,Short summary
As using deep learning algorithms has become a popular data analytic technique, atmospheric scientists should have a balanced perception of their strengths and limitations so that they can provide a powerful analysis of complex data with well-established procedures. This study addresses significant limitations of an advanced deep learning algorithm, the convolutional neural network.
Eemeli Holopainen, Harri Kokkola, Anton Laakso, and Thomas Kühn
Geosci. Model Dev., 13, 6215–6235,Short summary
This paper introduces an in-cloud wet deposition scheme for liquid and ice phase clouds for global aerosol–climate models. With the default setup, our wet deposition scheme behaves spuriously and better representation can be achieved with this scheme when black carbon is mixed with soluble compounds at emission time. This work is done as many of the global models fail to reproduce the transport of black carbon to the Arctic, which may be due to the poor representation of wet removal in models.
Travis A. O'Brien, Mark D. Risser, Burlen Loring, Abdelrahman A. Elbashandy, Harinarayan Krishnan, Jeffrey Johnson, Christina M. Patricola, John P. O'Brien, Ankur Mahesh, Prabhat, Sarahí Arriaga Ramirez, Alan M. Rhoades, Alexander Charn, Héctor Inda Díaz, and William D. Collins
Geosci. Model Dev., 13, 6131–6148,Short summary
Researchers utilize various algorithms to identify extreme weather features in climate data, and we seek to answer this question: given a
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Enrique Pravia-Sarabia, Juan José Gómez-Navarro, Pedro Jiménez-Guerrero, and Juan Pedro Montávez
Geosci. Model Dev., 13, 6051–6075,Short summary
This work shows TITAM, a time-independent tracking algorithm specifically suited for Mediterranean tropical-like cyclones, often referred to as medicanes. The methodology developed has the capacity to track multiple simultaneous cyclones, the ability to track a medicane in the presence of intense extratropical lows, and the potential to separate the medicane from other similar structures by handling the intermittent loss of structure and managing the tilting of the axis.
Liang Guo, Ruud J. van der Ent, Nicholas P. Klingaman, Marie-Estelle Demory, Pier Luigi Vidale, Andrew G. Turner, Claudia C. Stephan, and Amulya Chevuturi
Geosci. Model Dev., 13, 6011–6028,Short summary
Precipitation over East Asia simulated in the Met Office Unified Model is compared with observations. Moisture sources of EA precipitation are traced using a moisture tracking model. Biases in moisture sources are linked to biases in precipitation. Using the tracking model, changes in moisture sources can be attributed to changes in SST, circulation and associated evaporation. This proves that the method used in this study is useful to identify the causes of biases in regional precipitation.
Ondřej Tichý, Lukáš Ulrych, Václav Šmídl, Nikolaos Evangeliou, and Andreas Stohl
Geosci. Model Dev., 13, 5917–5934,Short summary
We study the estimation of the temporal profile of an atmospheric release using formalization as a linear inverse problem. The problem is typically ill-posed, so all state-of-the-art methods need some form of regularization using additional information. We provide a sensitivity study on the prior source term and regularization parameters for the shape of the source term with a demonstration on the ETEX experimental release and the Cs-134 and Cs-137 dataset from the Chernobyl accident.
Laura Palacios-Peña, Jerome D. Fast, Enrique Pravia-Sarabia, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 13, 5897–5915,Short summary
The main objective of this work is to study the impact of the representation of aerosol size distribution on aerosol optical properties over central Europe and the Mediterranean Basin during a summertime aerosol episode using the WRF-Chem online model. Results reveal that the reduction in the standard deviation of the accumulation mode leads to the largest impacts on aerosol optical depth (AOD) representation due to a transfer of particles from the accumulation mode to the coarse mode.
Yilong Wang, Grégoire Broquet, François-Marie Bréon, Franck Lespinas, Michael Buchwitz, Maximilian Reuter, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, and Philippe Ciais
Geosci. Model Dev., 13, 5813–5831,
Marek Jacob, Pavlos Kollias, Felix Ament, Vera Schemann, and Susanne Crewell
Geosci. Model Dev., 13, 5757–5777,Short summary
We compare clouds in different cloud-resolving atmosphere simulations with airborne remote sensing observations. The focus is on warm shallow clouds in the Atlantic trade wind region. Those clouds are climatologically important but challenging for climate models. We use forward operators to apply instrument-specific thresholds for cloud detection to model outputs. In this comparison, the higher-resolution model better reproduces the layered cloud structure.
Setigui Aboubacar Keita, Eric Girard, Jean-Christophe Raut, Maud Leriche, Jean-Pierre Blanchet, Jacques Pelon, Tatsuo Onishi, and Ana Cirisan
Geosci. Model Dev., 13, 5737–5755,
Bart Degraeuwe, Enrico Pisoni, and Philippe Thunis
Geosci. Model Dev., 13, 5725–5736,Short summary
To make decisions on how to improve air quality, it is useful to identify the main sources of pollution for an area of interest. Often these sources of pollution are identified with complex models that, even if accurate, are time consuming and complex. In this work we use another approach, simplified models, to accomplish the same task. The results, computed with two different set of simplified models, show the main sources of pollution for selected cities, and the associated uncertainties.
Mathieu Lachatre, Sylvain Mailler, Laurent Menut, Solène Turquety, Pasquale Sellitto, Henda Guermazi, Giuseppe Salerno, Tommaso Caltabiano, and Elisa Carboni
Geosci. Model Dev., 13, 5707–5723,Short summary
Excessive numerical diffusion is a major limitation in the representation of long-range transport in atmospheric models. In the present study, we focus on excessive diffusion in the vertical direction. We explore three possible ways of addressing this problem: increased vertical resolution, an advection scheme with anti-diffusive properties and more accurate representation of vertical wind. This study focused on a particular volcanic eruption event to improve atmospheric transport modeling.
Mona Kurppa, Pontus Roldin, Jani Strömberg, Anna Balling, Sasu Karttunen, Heino Kuuluvainen, Jarkko V. Niemi, Liisa Pirjola, Topi Rönkkö, Hilkka Timonen, Antti Hellsten, and Leena Järvi
Geosci. Model Dev., 13, 5663–5685,Short summary
High-resolution modelling is needed to solve the aerosol concentrations in a complex urban area. Here, the performance of an aerosol module within the PALM model to simulate the detailed horizontal and vertical distribution of aerosol particles is studied. Further, sensitivity to the meteorological and aerosol boundary conditions is assessed using both model and observation data. The horizontal distribution is sensitive to the wind speed and stability, and the vertical to the wind direction.
Robert Schoetter, Yu Ting Kwok, Cécile de Munck, Kevin Ka Lun Lau, Wai Kin Wong, and Valéry Masson
Geosci. Model Dev., 13, 5609–5643,Short summary
Cities change the local meteorological conditions, e.g. by increasing air temperature, which can negatively impact humans and infrastructure. The urban climate model TEB is able to calculate the meteorological conditions in low- and mid-rise cities since it interacts with the lowest level of an atmospheric model. Here, a multi-layer coupling of TEB is introduced to enable modelling the urban climate of cities with many skyscrapers; the new version is tested for the high-rise city of Hong Kong.
Stelios Myriokefalitakis, Nikos Daskalakis, Angelos Gkouvousis, Andreas Hilboll, Twan van Noije, Jason E. Williams, Philippe Le Sager, Vincent Huijnen, Sander Houweling, Tommi Bergman, Johann Rasmus Nüß, Mihalis Vrekoussis, Maria Kanakidou, and Maarten C. Krol
Geosci. Model Dev., 13, 5507–5548,Short summary
This work documents and evaluates the detailed tropospheric gas-phase chemical mechanism MOGUNTIA in the three-dimensional chemistry transport model TM5-MP. The Rosenbrock solver, as generated by the KPP software, is implemented in the chemistry code, which can successfully replace the classical Euler backward integration method. The MOGUNTIA scheme satisfactorily simulates a large suite of oxygenated volatile organic compounds (VOCs) that are observed in the atmosphere at significant levels.
Alejandro Luque, Francisco José Gordillo-Vázquez, Dongshuai Li, Alejandro Malagón-Romero, Francisco Javier Pérez-Invernón, Anthony Schmalzried, Sergio Soler, Olivier Chanrion, Matthias Heumesser, Torsten Neubert, Víctor Reglero, and Nikolai Østgaard
Geosci. Model Dev., 13, 5549–5566,Short summary
Lightning flashes are often recorded from space-based platforms. Besides being valuable inputs for weather forecasting, these observations also enable research into fundamental questions regarding lightning physics. To exploit them, it is essential to understand how light propagates from a lightning flash to a space-based observation instrument. Here, we present an open-source software tool to model this process that extends on previous work and overcomes some of the existing limitations.
Yuefei Zeng, Alberto de Lozar, Tijana Janjic, and Axel Seifert
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
A new integrated mass-flux adjustment filter is introduced and examined by an idealized setup for convective-scale radar data assimilation. It is found that the new filter slightly reduce the accuracy of background and analysis states, however, it preserves the main structure of cold pools and primary mesocyclone properties of supercells. More importantly, it considerably diminishes successfully imbalance in the analysis and improves the forecasts.
Anne Tipka, Leopold Haimberger, and Petra Seibert
Geosci. Model Dev., 13, 5277–5310,Short summary
Flex_extract v7.1 is an open-source software to retrieve and prepare meteorological fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) MARS archive to serve as input for the FLEXTRA–FLEXPART atmospheric transport modelling system. It can be used by public as well as member-state users and enables the retrieval of a variety of different data sets, including the new reanalysis ERA5. Instructions are given for installation along with typical usage scenarios.
Almudena García-García, Francisco José Cuesta-Valero, Hugo Beltrami, Fidel González-Rouco, Elena García-Bustamante, and Joel Finnis
Geosci. Model Dev., 13, 5345–5366,
Robin D. Lamboll, Zebedee R. J. Nicholls, Jarmo S. Kikstra, Malte Meinshausen, and Joeri Rogelj
Geosci. Model Dev., 13, 5259–5275,Short summary
Many models project how human activity can lead to more or less climate change, but most of these models do not project all climate-relevant emissions, potentially biasing climate projections. This paper outlines a Python package called Silicone, which can add missing emissions in a flexible yet high-throughput manner. It does this
infillingbased on more complete literature projections. It facilitates a more complete understanding of the climate impact of alternative emission pathways.
Michael Weger, Oswald Knoth, and Bernd Heinold
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
A new numerical air-quality transport model for cities is presented, in which buildings are described diffusively. The used diffusive-obstacles approach, helps to reduce the computational costs for high-resolution simulations as the grid spacing can be more coarse than in traditional approaches. The research which led to this model development was primarily motivated by the need of a computationally feasible downscaling tool for urban wind and pollution fields from meteorological model output.
Simon Unterstrasser, Fabian Hoffmann, and Marion Lerch
Geosci. Model Dev., 13, 5119–5145,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.
Andrea N. Hahmann, Tija Sīle, Björn Witha, Neil N. Davis, Martin Dörenkämper, Yasemin Ezber, Elena García-Bustamante, J. Fidel González-Rouco, Jorge Navarro, Bjarke T. Olsen, and Stefan Söderberg
Geosci. Model Dev., 13, 5053–5078,Short summary
Wind energy resource assessment routinely uses numerical weather prediction model output. We describe the evaluation procedures used for picking the suitable blend of model setup and parameterizations for simulating European wind climatology with the WRF model. We assess the simulated winds against tall mast measurements using a suite of metrics, including the Earth Mover's Distance, which diagnoses the performance of each ensemble member using the full wind speed and direction distribution.
Martin Dörenkämper, Bjarke T. Olsen, Björn Witha, Andrea N. Hahmann, Neil N. Davis, Jordi Barcons, Yasemin Ezber, Elena García-Bustamante, J. Fidel González-Rouco, Jorge Navarro, Mariano Sastre-Marugán, Tija Sīle, Wilke Trei, Mark Žagar, Jake Badger, Julia Gottschall, Javier Sanz Rodrigo, and Jakob Mann
Geosci. Model Dev., 13, 5079–5102,Short summary
This is the second of two papers that document the creation of the New European Wind Atlas (NEWA). The paper includes a detailed description of the technical and practical aspects that went into running the mesoscale simulations and the microscale downscaling for generating the climatology. A comprehensive evaluation of each component of the NEWA model chain is presented using observations from a large set of tall masts located all over Europe.
Lukas H. Leufen, Felix Kleinert, and Martin G. Schultz
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
MLAir provides a coherent end-to-end structure for a typical time series analysis workflow using machine learning (ML). Yet, it is adaptable to a variety of ML use cases. The user has a free hand with the ML model itself and can select from different methods during preprocessing, training, and postprocessing. MLAir offers tools to track the experiment conduction, documents the necessary ML parameters, and creates a variety of publication-ready plots.
Axel Kleidon and Lee M. Miller
Geosci. Model Dev., 13, 4993–5005,Short summary
When winds are used as renewable energy by more and more wind turbines, one needs to account for the effect of wind turbines on the atmospheric flow. The Kinetic Energy Budget of the Atmosphere (KEBA) model provides a simple, physics-based approach to account for this effect very well when compared to much more detailed numerical simulations with an atmospheric model. KEBA should be useful to derive lower, more realistic wind energy resource potentials of different regions.
Isabella Capel-Timms, Stefán Thor Smith, Ting Sun, and Sue Grimmond
Geosci. Model Dev., 13, 4891–4924,Short summary
Thermal emissions or anthropogenic heat fluxes (QF) from human activities impact the local- and larger-scale urban climate. DASH considers both urban form and function in simulating QF by use of an agent-based structure that includes behavioural characteristics of city populations. This allows social practices to drive the calculation of QF as occupants move, varying by day type, demographic, location, activity, and socio-economic factors and in response to environmental conditions.
Paul-Arthur Monerie, Amulya Chevuturi, Peter Cook, Nicholas P. Klingaman, and Christopher E. Holloway
Geosci. Model Dev., 13, 4749–4771,Short summary
In this study, we assess how increasing the horizontal resolution of HadGEM3-GC31 can allow simulating better tropical and subtropical South American precipitation. We compare simulations of HadGEM3-GC3.1, performed at three different horizontal resolutions. We show that increasing resolution allows decreasing precipitation biases over the Andes and northeast Brazil and improves the simulation of daily precipitation distribution.
Guangzhi Xu, Xiaohui Ma, Ping Chang, and Lin Wang
Geosci. Model Dev., 13, 4639–4662,Short summary
We observed considerable limitations in existing atmospheric river (AR) detection methods and looked into other disciplines for inspirations of tackling the AR detection problem. A new method is derived from an image-processing technique and encodes the spatiotemporal-scale information of AR systems, which is a key physical ingredient of ARs that is more stable than the vapor flux intensities, making it more suitable for climate-scale studies when models often have different biases.
Sarah Sparrow, Andrew Bowery, Glenn D. Carver, Marcus O. Köhler, Pirkka Ollinaho, Florian Pappenberger, David Wallom, and Antje Weisheimer
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
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 realisations of the tropical storm Karl to demonstrate the performance of the large ensemble forecast. OpenIFS@Home offers researchers a new tool to study weather forecasts and related questions.
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