Articles | Volume 15, issue 18
https://doi.org/10.5194/gmd-15-7139-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-7139-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
22 Sep 2022
Model description paper |
| 22 Sep 2022
MultilayerPy (v1.0): a Python-based framework for building, running and optimising kinetic multi-layer models of aerosols and films
Adam Milsom
School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK
Amy Lees
School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK
Adam M. Squires
Department of Chemistry, University of Bath, South Building, Soldier Down Ln, Claverton Down, Bath, UK
School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK
Department of Meteorology, University of Reading, Whiteknights, Earley Gate, Reading, UK
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Adam Milsom, Shaojun Qi, Ashmi Mishra, Thomas Berkemeier, Zhenyu Zhang, and Christian Pfrang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1207, https://doi.org/10.5194/egusphere-2023-1207, 2023
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Aerosols and films are found indoors and outdoors. Our study measures and models reactions of a cooking aerosol proxy with the atmospheric oxidant ozone relying on a low-cost, but sensitive technique based on mass changes and film rigidity. We found that film morphology changed and film rigidity increased with evidence of surface crust formation during ozone exposure. Our modelling results demonstrate clear potential to take this robust method to the field for reaction monitoring.
Sophie A. Mills, Adam Milsom, Christian Pfrang, A. Rob MacKenzie, and Francis D. Pope
EGUsphere, https://doi.org/10.5194/egusphere-2023-670, https://doi.org/10.5194/egusphere-2023-670, 2023
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Pollen are important components of the atmosphere, which have the potential to impact upon cloud processes, through their ability to help in the formation of rain droplets. This study investigates the hygroscopicity of two different pollen species using an acoustic levitator. Pollen grains are levitated and their response to changes in relative humidity are investigated. A key advantage of this method is that it is possible study pollen shape under the varying environmental conditions.
Adam Milsom, Adam M. Squires, Andrew D. Ward, and Christian Pfrang
Atmos. Chem. Phys., 22, 4895–4907, https://doi.org/10.5194/acp-22-4895-2022, https://doi.org/10.5194/acp-22-4895-2022, 2022
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Cooking emissions can self-organise into nanostructured lamellar bilayers, and this can influence reaction kinetics. We developed a kinetic multi-layer model-based description of decay data we obtained from laboratory experiments of the ozonolysis of coated films of such a self-organised system, demonstrating a decreased diffusivity for both oleic acid and ozone. Nanostructure formation can thus increase the reactive half-life of oleic acid by days under typical indoor and outdoor conditions.
Adam Milsom, Adam M. Squires, Jacob A. Boswell, Nicholas J. Terrill, Andrew D. Ward, and Christian Pfrang
Atmos. Chem. Phys., 21, 15003–15021, https://doi.org/10.5194/acp-21-15003-2021, https://doi.org/10.5194/acp-21-15003-2021, 2021
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Atmospheric aerosols can be solid, semi-solid or liquid. This phase state may impact key aerosol processes such as oxidation and water uptake, affecting cloud droplet formation and urban air pollution. We have observed a solid crystalline organic phase in a levitated proxy for cooking emissions, oleic acid. Spatially resolved structural changes were followed during ageing by X-ray scattering, revealing phase gradients, aggregate products and a markedly reduced ozonolysis reaction rate.
Benjamin Woden, Maximilian W. A. Skoda, Adam Milsom, Curtis Gubb, Armando Maestro, James Tellam, and Christian Pfrang
Atmos. Chem. Phys., 21, 1325–1340, https://doi.org/10.5194/acp-21-1325-2021, https://doi.org/10.5194/acp-21-1325-2021, 2021
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Atmospheric aerosols contain a large amount of organic compounds, whose oxidation affects their physical properties through a process known as ageing. We have simulated atmospheric ageing experimentally to elucidate the nature and behaviour of residual surface films. Our results show an increasing amount of residue at near-zero temperatures, demonstrating that an inert product film may build up during droplet ageing, even if only ordinarily short-lived reactive species are initially emitted.
Adam Milsom, Shaojun Qi, Ashmi Mishra, Thomas Berkemeier, Zhenyu Zhang, and Christian Pfrang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1207, https://doi.org/10.5194/egusphere-2023-1207, 2023
Short summary
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Aerosols and films are found indoors and outdoors. Our study measures and models reactions of a cooking aerosol proxy with the atmospheric oxidant ozone relying on a low-cost, but sensitive technique based on mass changes and film rigidity. We found that film morphology changed and film rigidity increased with evidence of surface crust formation during ozone exposure. Our modelling results demonstrate clear potential to take this robust method to the field for reaction monitoring.
Sophie A. Mills, Adam Milsom, Christian Pfrang, A. Rob MacKenzie, and Francis D. Pope
EGUsphere, https://doi.org/10.5194/egusphere-2023-670, https://doi.org/10.5194/egusphere-2023-670, 2023
Short summary
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Pollen are important components of the atmosphere, which have the potential to impact upon cloud processes, through their ability to help in the formation of rain droplets. This study investigates the hygroscopicity of two different pollen species using an acoustic levitator. Pollen grains are levitated and their response to changes in relative humidity are investigated. A key advantage of this method is that it is possible study pollen shape under the varying environmental conditions.
Adam Milsom, Adam M. Squires, Andrew D. Ward, and Christian Pfrang
Atmos. Chem. Phys., 22, 4895–4907, https://doi.org/10.5194/acp-22-4895-2022, https://doi.org/10.5194/acp-22-4895-2022, 2022
Short summary
Short summary
Cooking emissions can self-organise into nanostructured lamellar bilayers, and this can influence reaction kinetics. We developed a kinetic multi-layer model-based description of decay data we obtained from laboratory experiments of the ozonolysis of coated films of such a self-organised system, demonstrating a decreased diffusivity for both oleic acid and ozone. Nanostructure formation can thus increase the reactive half-life of oleic acid by days under typical indoor and outdoor conditions.
Adam Milsom, Adam M. Squires, Jacob A. Boswell, Nicholas J. Terrill, Andrew D. Ward, and Christian Pfrang
Atmos. Chem. Phys., 21, 15003–15021, https://doi.org/10.5194/acp-21-15003-2021, https://doi.org/10.5194/acp-21-15003-2021, 2021
Short summary
Short summary
Atmospheric aerosols can be solid, semi-solid or liquid. This phase state may impact key aerosol processes such as oxidation and water uptake, affecting cloud droplet formation and urban air pollution. We have observed a solid crystalline organic phase in a levitated proxy for cooking emissions, oleic acid. Spatially resolved structural changes were followed during ageing by X-ray scattering, revealing phase gradients, aggregate products and a markedly reduced ozonolysis reaction rate.
Benjamin Woden, Maximilian W. A. Skoda, Adam Milsom, Curtis Gubb, Armando Maestro, James Tellam, and Christian Pfrang
Atmos. Chem. Phys., 21, 1325–1340, https://doi.org/10.5194/acp-21-1325-2021, https://doi.org/10.5194/acp-21-1325-2021, 2021
Short summary
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Atmospheric aerosols contain a large amount of organic compounds, whose oxidation affects their physical properties through a process known as ageing. We have simulated atmospheric ageing experimentally to elucidate the nature and behaviour of residual surface films. Our results show an increasing amount of residue at near-zero temperatures, demonstrating that an inert product film may build up during droplet ageing, even if only ordinarily short-lived reactive species are initially emitted.
Mohammed S. Alam, Leigh R. Crilley, James D. Lee, Louisa J. Kramer, Christian Pfrang, Mónica Vázquez-Moreno, Milagros Ródenas, Amalia Muñoz, and William J. Bloss
Atmos. Meas. Tech., 13, 5977–5991, https://doi.org/10.5194/amt-13-5977-2020, https://doi.org/10.5194/amt-13-5977-2020, 2020
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We report on the interference arising in measurements of nitrogen oxides (NOx) from the presence of a range of alkenes in sampled air when using the most widespread air quality monitoring technique for chemiluminescence detection. Interferences of up to 11 % are reported, depending upon the alkene present and conditions used. Such interferences may be of substantial importance for the interpretation of ambient NOx data, particularly for high volatile organic compound and low NOx environments.
Federica Sebastiani, Richard A. Campbell, Kunal Rastogi, and Christian Pfrang
Atmos. Chem. Phys., 18, 3249–3268, https://doi.org/10.5194/acp-18-3249-2018, https://doi.org/10.5194/acp-18-3249-2018, 2018
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We report the first kinetic study of a key atmospheric nighttime oxidant (NO3) with one-molecule thin organic layers at the air–water interface. Organic molecules were chosen to establish the impact of head group, aliphatic chain length and saturation. We show that NO3 may dominate degradation at night, retention of the organic character varies strongly and atmospheric lifetimes are longer than those determined at the interface – a key motivation for further experimental and modelling studies.
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Zhenxin Liu, Yuanhao Chen, Yuhang Wang, Cheng Liu, Shuhua Liu, and Hong Liao
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Kai Cao, Qizhong Wu, Lingling Wang, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongqing Li, and Lanning Wang
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Offline performance experiment results show that the GPU-HADVPPM on a V100 GPU can achieve up to 1113.6 × speedups to its original version on an E5-2682 v4 CPU. A series of optimization measures are taken, and the CAMx-CUDA model improves the computing efficiency by 128.4 × on a single V100 GPU card. A parallel architecture with an MPI plus CUDA hybrid paradigm is presented, and it can achieve up to 4.5 × speedup when launching eight CPU cores and eight GPU cards.
Laurent Menut
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Emily de Jong, John Ben Mackay, Oleksii Bulenok, Anna Jaruga, and Sylwester Arabas
Geosci. Model Dev., 16, 4193–4211, https://doi.org/10.5194/gmd-16-4193-2023, https://doi.org/10.5194/gmd-16-4193-2023, 2023
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In clouds, collisional breakup occurs when two colliding droplets splinter into new, smaller fragments. Particle-based modeling approaches often do not represent breakup because of the computational demands of creating new droplets. We present a particle-based breakup method that preserves the computational efficiency of these methods. In a series of simple demonstrations, we show that this representation alters cloud processes in reasonable and expected ways.
Caiyi Jin, Qiangqiang Yuan, Tongwen Li, Yuan Wang, and Liangpei Zhang
Geosci. Model Dev., 16, 4137–4154, https://doi.org/10.5194/gmd-16-4137-2023, https://doi.org/10.5194/gmd-16-4137-2023, 2023
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The semi-empirical physical approach derives PM2.5 with strong physical significance. However, due to the complex optical characteristic, the physical parameters are difficult to express accurately. Thus, combining the atmospheric physical mechanism and machine learning, we propose an optimized model. It creatively embeds the random forest model into the physical PM2.5 remote sensing approach to simulate a physical parameter. Our method shows great optimized performance in the validations.
Cyril Caram, Sophie Szopa, Anne Cozic, Slimane Bekki, Carlos A. Cuevas, and Alfonso Saiz-Lopez
Geosci. Model Dev., 16, 4041–4062, https://doi.org/10.5194/gmd-16-4041-2023, https://doi.org/10.5194/gmd-16-4041-2023, 2023
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We studied the role of halogenated compounds (containing chlorine, bromine and iodine), emitted by natural processes (mainly above the oceans), in the chemistry of the lower layers of the atmosphere. We introduced this relatively new chemistry in a three-dimensional climate–chemistry model and looked at how this chemistry will disrupt the ozone. We showed that the concentration of ozone decreases by 22 % worldwide and that of the atmospheric detergent, OH, by 8 %.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev., 16, 3997–4016, https://doi.org/10.5194/gmd-16-3997-2023, https://doi.org/10.5194/gmd-16-3997-2023, 2023
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Monitoring of CO2 emissions is key to the development of reduction policies. Local emissions, from cities or power plants, may be estimated from CO2 plumes detected in satellite images. CO2 plumes generally have a weak signal and are partially concealed by highly variable background concentrations and instrument errors, which hampers their detection. To address this problem, we propose and apply deep learning methods to detect the contour of a plume in simulated CO2 satellite images.
Min-Seop Ahn, Paul A. Ullrich, Peter J. Gleckler, Jiwoo Lee, Ana C. Ordonez, and Angeline G. Pendergrass
Geosci. Model Dev., 16, 3927–3951, https://doi.org/10.5194/gmd-16-3927-2023, https://doi.org/10.5194/gmd-16-3927-2023, 2023
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We introduce a framework for regional-scale evaluation of simulated precipitation distributions with 62 climate reference regions and 10 metrics and apply it to evaluate CMIP5 and CMIP6 models against multiple satellite-based precipitation products. The common model biases identified in this study are mainly associated with the overestimated light precipitation and underestimated heavy precipitation. These biases persist from earlier-generation models and have been slightly improved in CMIP6.
Christine Wiedinmyer, Yosuke Kimura, Elena C. McDonald-Buller, Louisa K. Emmons, Rebecca R. Buchholz, Wenfu Tang, Keenan Seto, Maxwell B. Joseph, Kelley C. Barsanti, Annmarie G. Carlton, and Robert Yokelson
Geosci. Model Dev., 16, 3873–3891, https://doi.org/10.5194/gmd-16-3873-2023, https://doi.org/10.5194/gmd-16-3873-2023, 2023
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The Fire INventory from NCAR (FINN) provides daily global estimates of emissions from open fires based on satellite detections of hot spots. This version has been updated to apply MODIS and VIIRS satellite fire detection and better represents both large and small fires. FINNv2.5 generates more emissions than FINNv1 and is in general agreement with other fire emissions inventories. The new estimates are consistent with satellite observations, but uncertainties remain regionally and by pollutant.
Lichao Yang, Wansuo Duan, and Zifa Wang
Geosci. Model Dev., 16, 3827–3848, https://doi.org/10.5194/gmd-16-3827-2023, https://doi.org/10.5194/gmd-16-3827-2023, 2023
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An approach is proposed to refine a ground meteorological observation network to improve the PM2.5 forecasts in the Beijing–Tianjin–Hebei region. A cost-effective observation network is obtained and makes the relevant PM2.5 forecasts assimilate fewer observations but achieve the forecasting skill comparable to or higher than that obtained by assimilating all ground station observations, suggesting that many of the current ground stations can be greatly scattered to avoid much unnecessary work.
Abhishekh Kumar Srivastava, Paul Aaron Ullrich, Deeksha Rastogi, Pouya Vahmani, Andrew Jones, and Richard Grotjahn
Geosci. Model Dev., 16, 3699–3722, https://doi.org/10.5194/gmd-16-3699-2023, https://doi.org/10.5194/gmd-16-3699-2023, 2023
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Stakeholders need high-resolution regional climate data for applications such as assessing water availability and mountain snowpack. This study examines 3 h and 24 h historical precipitation over the contiguous United States in the 12 km WRF version 4.2.1-based dynamical downscaling of the ERA5 reanalysis. WRF improves precipitation characteristics such as the annual cycle and distribution of the precipitation maxima, but it also displays regionally and seasonally varying precipitation biases.
Haixia Xiao, Yaqiang Wang, Yu Zheng, Yuanyuan Zheng, Xiaoran Zhuang, Hongyan Wang, and Mei Gao
Geosci. Model Dev., 16, 3611–3628, https://doi.org/10.5194/gmd-16-3611-2023, https://doi.org/10.5194/gmd-16-3611-2023, 2023
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Due to the small-scale and nonstationary nature of convective wind gusts (CGs), reliable CG nowcasting has remained unattainable. Here, we developed a deep learning model — namely CGsNet — for 0—2 h of quantitative CG nowcasting, first achieving minute—kilometer-level forecasts. Based on the CGsNet model, the average surface wind speed (ASWS) and peak wind gust speed (PWGS) predictions are obtained. Experiments indicate that CGsNet exhibits higher accuracy than the traditional method.
Maria Krutova, Mostafa Bakhoday-Paskyabi, Joachim Reuder, and Finn Gunnar Nielsen
Geosci. Model Dev., 16, 3553–3564, https://doi.org/10.5194/gmd-16-3553-2023, https://doi.org/10.5194/gmd-16-3553-2023, 2023
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Local refinement of the grid is a powerful method allowing us to reduce the computational time while preserving the accuracy in the area of interest. Depending on the implementation, the local refinement may introduce unwanted numerical effects into the results. We study the wind speed common to the wind turbine operational speeds and confirm strong alteration of the result when the heat fluxes are present, except for the specific refinement scheme used.
Sylvia Sullivan, Behrooz Keshtgar, Nicole Albern, Elzina Bala, Christoph Braun, Anubhav Choudhary, Johannes Hörner, Hilke Lentink, Georgios Papavasileiou, and Aiko Voigt
Geosci. Model Dev., 16, 3535–3551, https://doi.org/10.5194/gmd-16-3535-2023, https://doi.org/10.5194/gmd-16-3535-2023, 2023
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Clouds absorb and re-emit infrared radiation from Earth's surface and absorb and reflect incoming solar radiation. As a result, they change atmospheric temperature gradients that drive large-scale circulation. To better simulate this circulation, we study how the radiative heating and cooling from clouds depends on model settings like grid spacing; whether we describe convection approximately or exactly; and the level of detail used to describe small-scale processes, or microphysics, in clouds.
Denis E. Sergeev, Nathan J. Mayne, Thomas Bendall, Ian A. Boutle, Alex Brown, Iva Kavcic, James Kent, Krisztian Kohary, James Manners, Thomas Melvin, Enrico Olivier, Lokesh K. Ragta, Ben J. Shipway, Jon Wakelin, Nigel Wood, and Mohamed Zerroukat
EGUsphere, https://doi.org/10.5194/egusphere-2023-647, https://doi.org/10.5194/egusphere-2023-647, 2023
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3D climate models are one of the best tools we have to study planetary atmospheres. Here, we apply LFRic-Atmosphere, a new model developed by the Met Office, to seven different scenarios for terrestrial planetary climates, including four for the exoplanet TRAPPIST-1e, a primary target for future observations. LFRic-Atmosphere reproduces these scenarios within the spread of the existing models across a range of key climatic variables, justifying its use in future exoplanet studies.
James Weber, James A. King, Katerina Sindelarova, and Maria Val Martin
Geosci. Model Dev., 16, 3083–3101, https://doi.org/10.5194/gmd-16-3083-2023, https://doi.org/10.5194/gmd-16-3083-2023, 2023
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The emissions of volatile organic compounds from vegetation (BVOCs) influence atmospheric composition and contribute to certain gases and aerosols (tiny airborne particles) which play a role in climate change. BVOC emissions are likely to change in the future due to changes in climate and land use. Therefore, accurate simulation of BVOC emission is important, and this study describes an update to the simulation of BVOC emissions in the United Kingdom Earth System Model (UKESM).
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081, https://doi.org/10.5194/gmd-16-3029-2023, https://doi.org/10.5194/gmd-16-3029-2023, 2023
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We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
Xueying Liu, Yuxuan Wang, Shailaja Wasti, Wei Li, Ehsan Soleimanian, James Flynn, Travis Griggs, Sergio Alvarez, John T. Sullivan, Maurice Roots, Laurence Twigg, Guillaume Gronoff, Timothy Berkoff, Paul Walter, Mark Estes, Johnathan W. Hair, Taylor Shingler, Amy Jo Scarino, Marta Fenn, and Laura Judd
EGUsphere, https://doi.org/10.5194/egusphere-2023-892, https://doi.org/10.5194/egusphere-2023-892, 2023
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With a comprehensive suite of ground-based and airborne remote sensing measurements during the 2021 Tracking Aerosol Convection Experiment Air Quality (TRACER-AQ) campaign in Houston, this study evaluates the simulation of the planetary boundary layer (PBL) height and the ozone vertical profile by a high-resolution (1.33 km) 3-D photochemical model Weather Research and Forecasting-driven GEOS-Chem (WRF-GC).
Xiaohan Li, Yi Zhang, Xindong Peng, Baiquan Zhou, Jian Li, and Yiming Wang
Geosci. Model Dev., 16, 2975–2993, https://doi.org/10.5194/gmd-16-2975-2023, https://doi.org/10.5194/gmd-16-2975-2023, 2023
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The weather and climate physics suites used in GRIST-A22.7.28 are compared using single-column modeling. The source of their discrepancies in terms of modeling cloud and precipitation is explored. Convective parameterization is found to be a key factor responsible for the differences. The two suites also have intrinsic differences in the interaction between microphysics and other processes, resulting in different cloud features and time step sensitivities.
Virginie Marécal, Ronan Voisin-Plessis, Tjarda Jane Roberts, Alessandro Aiuppa, Herizo Narivelo, Paul David Hamer, Béatrice Josse, Jonathan Guth, Luke Surl, and Lisa Grellier
Geosci. Model Dev., 16, 2873–2898, https://doi.org/10.5194/gmd-16-2873-2023, https://doi.org/10.5194/gmd-16-2873-2023, 2023
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We implemented a halogen volcanic chemistry scheme in a one-dimensional modelling framework preparing for further use in a three-dimensional global chemistry-transport model. The results of the simulations for an eruption of Mt Etna in 2008, including various sensitivity tests, show a good consistency with previous modelling studies.
Zhe Feng, Joseph Hardin, Hannah C. Barnes, Jianfeng Li, L. Ruby Leung, Adam Varble, and Zhixiao Zhang
Geosci. Model Dev., 16, 2753–2776, https://doi.org/10.5194/gmd-16-2753-2023, https://doi.org/10.5194/gmd-16-2753-2023, 2023
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PyFLEXTRKR is a flexible atmospheric feature tracking framework with specific capabilities to track convective clouds from a variety of observations and model simulations. The package has a collection of multi-object identification algorithms and has been optimized for large datasets. This paper describes the algorithms and demonstrates applications for tracking deep convective cells and mesoscale convective systems from observations and model simulations at a wide range of scales.
Yan Ji, Bing Gong, Michael Langguth, Amirpasha Mozaffari, and Xiefei Zhi
Geosci. Model Dev., 16, 2737–2752, https://doi.org/10.5194/gmd-16-2737-2023, https://doi.org/10.5194/gmd-16-2737-2023, 2023
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Formulating short-term precipitation forecasting as a video prediction task, a novel deep learning architecture (convolutional long short-term memory generative adversarial network, CLGAN) is proposed. A benchmark dataset is built on minute-level precipitation measurements. Results show that with the GAN component the model generates predictions sharing statistical properties with observations, resulting in it outperforming the baseline in dichotomous and spatial scores for heavy precipitation.
Aleksander Lacima, Hervé Petetin, Albert Soret, Dene Bowdalo, Oriol Jorba, Zhaoyue Chen, Raúl F. Méndez Turrubiates, Hicham Achebak, Joan Ballester, and Carlos Pérez García-Pando
Geosci. Model Dev., 16, 2689–2718, https://doi.org/10.5194/gmd-16-2689-2023, https://doi.org/10.5194/gmd-16-2689-2023, 2023
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Understanding how air pollution varies across space and time is of key importance for the safeguarding of human health. This work arose in the context of the project EARLY-ADAPT, for which the Barcelona Supercomputing Center developed an air pollution database covering all of Europe. Through different statistical methods, we compared two global pollution models against measurements from ground stations and found significant discrepancies between the observed and the modeled surface pollution.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
EGUsphere, https://doi.org/10.5194/egusphere-2023-876, https://doi.org/10.5194/egusphere-2023-876, 2023
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To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and evaluate modeled results against TROPOMI v2 over multiple power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind direction and prior emissions.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-69, https://doi.org/10.5194/gmd-2023-69, 2023
Preprint under review for GMD
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It's important to know how well atmospheric models do in the mountains, but there aren't very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado river basin against the data that's available. The model works pretty well but, there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we couldn't before.
Andrew Geiss, Po-Lun Ma, Balwinder Singh, and Joseph C. Hardin
Geosci. Model Dev., 16, 2355–2370, https://doi.org/10.5194/gmd-16-2355-2023, https://doi.org/10.5194/gmd-16-2355-2023, 2023
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Atmospheric aerosols play a critical role in Earth's climate, but it is too computationally expensive to directly model their interaction with radiation in climate simulations. This work develops a new neural-network-based parameterization of aerosol optical properties for use in the Energy Exascale Earth System Model that is much more accurate than the current one; it also introduces a unique model optimization method that involves randomly generating neural network architectures.
Joey C. Y. Lam, Amos P. K. Tai, Jason A. Ducker, and Christopher D. Holmes
Geosci. Model Dev., 16, 2323–2342, https://doi.org/10.5194/gmd-16-2323-2023, https://doi.org/10.5194/gmd-16-2323-2023, 2023
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We developed a new component within an atmospheric chemistry model to better simulate plant ecophysiological processes relevant for ozone air quality. We showed that it reduces simulated biases in plant uptake of ozone in prior models. The new model enables us to explore how future climatic changes affect air quality via affecting plants, examine ozone–vegetation interactions and feedbacks, and evaluate the impacts of changing atmospheric chemistry and climate on vegetation productivity.
Qian Shu, Sergey L. Napelenok, William T. Hutzell, Kirk R. Baker, Barron H. Henderson, Benjamin N. Murphy, and Christian Hogrefe
Geosci. Model Dev., 16, 2303–2322, https://doi.org/10.5194/gmd-16-2303-2023, https://doi.org/10.5194/gmd-16-2303-2023, 2023
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Source attribution methods are generally used to determine culpability of precursor emission sources to ambient pollutant concentrations. However, source attribution of secondarily formed pollutants such as ozone and its precursors cannot be explicitly measured, making evaluation of source apportionment methods challenging. In this study, multiple apportionment approach comparisons show common features but still reveal wide variations in predicted sector contribution and species dependency.
Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, and Terry Deshler
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-79, https://doi.org/10.5194/gmd-2023-79, 2023
Revised manuscript accepted for GMD
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We implemented an alternative aerosol scheme in the high and low-top model versions of the Community Earth System Model Version 2 (CESM2) with a more detailed description of tropospheric and stratospheric aerosol size distributions than the existing aerosol model. The development enables the comparison of different aerosol schemes with different complexity in the same model framework and identifies improvements in comparison to a range of observations in both the troposphere and stratosphere.
Rüdiger Brecht, Lucie Bakels, Alex Bihlo, and Andreas Stohl
Geosci. Model Dev., 16, 2181–2192, https://doi.org/10.5194/gmd-16-2181-2023, https://doi.org/10.5194/gmd-16-2181-2023, 2023
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We use neural-network-based single-image super-resolution to improve the upscaling of meteorological wind fields to be used for particle dispersion models. This deep-learning-based methodology improves the standard linear interpolation typically used in particle dispersion models. The improvement of wind fields leads to substantial improvement in the computed trajectories of the particles.
Alvaro Criado, Jan Mateu Armengol, Hervé Petetin, Daniel Rodriguez-Rey, Jaime Benavides, Marc Guevara, Carlos Pérez García-Pando, Albert Soret, and Oriol Jorba
Geosci. Model Dev., 16, 2193–2213, https://doi.org/10.5194/gmd-16-2193-2023, https://doi.org/10.5194/gmd-16-2193-2023, 2023
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This work aims to derive and evaluate a general statistical post-processing tool specifically designed for the street scale that can be applied to any urban air quality system. Our data fusion methodology corrects NO2 fields based on continuous hourly observations and experimental campaigns. This study enables us to obtain exceedance probability maps of air quality standards. In 2019, 13 % of the Barcelona area had a 70 % or higher probability of exceeding the annual legal NO2 limit of 40 µg/m3.
Liang Wang, Bingcheng Wan, Shaohui Zhou, Haofei Sun, and Zhiqiu Gao
Geosci. Model Dev., 16, 2167–2179, https://doi.org/10.5194/gmd-16-2167-2023, https://doi.org/10.5194/gmd-16-2167-2023, 2023
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The past 24 h TC trajectories and meteorological field data were used to forecast TC tracks in the northwestern Pacific from hours 6–72 based on GRU_CNN, which we proposed in this paper and which has better prediction results than traditional single deep-learning methods. The historical steering flow of cyclones has a significant effect on improving the accuracy of short-term forecasting, while, in long-term forecasting, the SST and geopotential height will have a particular impact.
Roland Eichinger, Sebastian Rhode, Hella Garny, Peter Preusse, Petr Pisoft, Aleš Kuchar, Patrick Jöckel, Astrid Kerkweg, and Bastian Kern
EGUsphere, https://doi.org/10.5194/egusphere-2023-270, https://doi.org/10.5194/egusphere-2023-270, 2023
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Dynamical model biases result from the columnar approach of gravity wave (GW) schemes, but parallel decomposition makes horizontal GW propagation computationally unfeasible. In the global model EMAC, we approximate it by GW redistribution at one altitude using tailor-made redistribution maps generated with a ray-tracer. More spread-out GW drag helps reconciling the model with observations and closing the 60S GW gap. Polar vortex dynamics are improved, enhancing climate model credibility.
Thibaud Sarica, Alice Maison, Yelva Roustan, Matthias Ketzel, Steen Solvang Jensen, Youngseob Kim, Christophe Chaillou, and Karine Sartelet
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-70, https://doi.org/10.5194/gmd-2023-70, 2023
Revised manuscript accepted for GMD
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A new version of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) is developed to represent heterogeneities of concentrations in streets. The street volume is discretized vertically and horizontally to limit the artificial dilution of emissions and concentrations. This new version is applied to street networks in Copenhagen and Paris. The comparisons to observations are improved, with higher concentrations of pollutants emitted by traffic at the bottom of the street.
Thomas Berkemeier, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger
Geosci. Model Dev., 16, 2037–2054, https://doi.org/10.5194/gmd-16-2037-2023, https://doi.org/10.5194/gmd-16-2037-2023, 2023
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Kinetic multi-layer models (KMs) successfully describe heterogeneous and multiphase atmospheric chemistry. In applications requiring repeated execution, however, these models can be too expensive. We trained machine learning surrogate models on output of the model KM-SUB and achieved high correlations. The surrogate models run orders of magnitude faster, which suggests potential applicability in global optimization tasks and as sub-modules in large-scale atmospheric models.
Elena Fillola, Raul Santos-Rodriguez, Alistair Manning, Simon O'Doherty, and Matt Rigby
Geosci. Model Dev., 16, 1997–2009, https://doi.org/10.5194/gmd-16-1997-2023, https://doi.org/10.5194/gmd-16-1997-2023, 2023
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Lagrangian particle dispersion models are used extensively for the estimation of greenhouse gas (GHG) fluxes using atmospheric observations. However, these models do not scale well as data volumes increase. Here, we develop a proof-of-concept machine learning emulator that can produce outputs similar to those of the dispersion model, but 50 000 times faster, using only meteorological inputs. This works demonstrates the potential of machine learning to accelerate GHG estimations across the globe.
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
EGUsphere, https://doi.org/10.5194/egusphere-2023-357, https://doi.org/10.5194/egusphere-2023-357, 2023
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Precipitation collects airborne particles and deposits these on the ground. This process is called wet deposition and greatly determines how airborne radioactive particles (released routinely or accidental) contaminate the surface. In this work we present a new method to improve the calculation of wet deposition in computer models. We apply this method to the existing model FLEXPART by simulating the Fukushima nuclear accident (2011), and show that it improves the simulation of wet deposition.
Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz
Geosci. Model Dev., 16, 1909–1924, https://doi.org/10.5194/gmd-16-1909-2023, https://doi.org/10.5194/gmd-16-1909-2023, 2023
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Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Cited articles
Abbatt, J. P. D. and Wang, C.:
The atmospheric chemistry of indoor environments, Environ. Sci.-Proc. Imp., 22, 25–48, https://doi.org/10.1039/c9em00386j, 2020.
Berkemeier, T., Ammann, M., Krieger, U. K., Peter, T., Spichtinger, P., Pöschl, U., Shiraiwa, M., and Huisman, A. J.:
Technical note: Monte Carlo genetic algorithm (MCGA) for model analysis of multiphase chemical kinetics to determine transport and reaction rate coefficients using multiple experimental data sets, Atmos. Chem. Phys., 17, 8021–8029, https://doi.org/10.5194/acp-17-8021-2017, 2017.
Berkemeier, T., Mishra, A., Mattei, C., Huisman, A. J., Krieger, U. K., and Pöschl, U.:
Ozonolysis of Oleic Acid Aerosol Revisited: Multiphase Chemical Kinetics and Reaction Mechanisms, ACS Earth Sp. Chem., 5, 3313–3323, https://doi.org/10.1021/acsearthspacechem.1c00232, 2021.
Dennis-Smither, B. J., Miles, R. E. H., and Reid, J. P.:
Oxidative aging of mixed oleic acid/sodium chloride aerosol particles, J. Geophys. Res.-Atmos., 117, 1–13, https://doi.org/10.1029/2012JD018163, 2012.
Foreman-Mackey, D., Hogg, D. W., Lang, D., and Goodman, J.:
emcee: The MCMC Hammer, Publ. Astron. Soc. Pac., 125, 306–312, https://doi.org/10.1086/670067, 2013.
Gallimore, P. J., Griffiths, P. T., Pope, F. D., Reid, J. P., and Kalberer, M.:
Comprehensive modeling study of ozonolysis of oleic acid aerosol based on real-time, online measurements of aerosol composition, J. Geophys. Res., 122, 4364–4377, https://doi.org/10.1002/2016JD026221, 2017.
González-Labrada, E., Schmidt, R., and DeWolf, C. E.:
Kinetic analysis of the ozone processing of an unsaturated organic monolayer as a model of an aerosol surface, Phys. Chem. Chem. Phys., 9, 5814–5821, https://doi.org/10.1039/b707890k, 2007.
Hearn, J. D. and Smith, G. D.:
Kinetics and product studies for ozonolysis reactions of organic particles using aerosol CIMS, J. Phys. Chem. A, 108, 10019–10029, https://doi.org/10.1021/jp0404145, 2004.
Hogg, D. W. and Foreman-Mackey, D.:
Data Analysis Recipes: Using Markov Chain Monte Carlo, Astrophys. J. Suppl. S., 236, 11, https://doi.org/10.3847/1538-4365/aab76e, 2018.
Hosny, N. A., Fitzgerald, C., Tong, C., Kalberer, M., Kuimova, M. K., and Pope, F. D.:
Fluorescent lifetime imaging of atmospheric aerosols: A direct probe of aerosol viscosity, Faraday Discuss., 165, 343–356, https://doi.org/10.1039/c3fd00041a, 2013.
Hosny, N. A., Fitzgerald, C., Vyšniauskas, A., Athanasiadis, A., Berkemeier, T., Uygur, N., Pöschl, U., Shiraiwa, M., Kalberer, M., Pope, F. D., and Kuimova, M. K.:
Direct imaging of changes in aerosol particle viscosity upon hydration and chemical aging, Chem. Sci., 7, 1357–1367, https://doi.org/10.1039/c5sc02959g, 2016.
Hua, A. K., Lakey, P. S. J., and Shiraiwa, M.:
Multiphase Kinetic Multilayer Model Interfaces for Simulating Surface and Bulk Chemistry for Environmental and Atmospheric Chemistry Teaching, J. Chem. Educ., 99, 1246–1254, https://doi.org/10.1021/acs.jchemed.1c00931, 2022.
Huang, L. and Topping, D.:
JlBox v1.1: a Julia-based multi-phase atmospheric chemistry box model, Geosci. Model Dev., 14, 2187–2203, https://doi.org/10.5194/gmd-14-2187-2021, 2021.
Huang, Y., Mahrt, F., Xu, S., Shiraiwa, M., Zuend, A., and Bertram, A. K.:
Coexistence of three liquid phases in individual atmospheric aerosol particles, P. Natl. Acad. Sci. USA, 118, e2102512118, https://doi.org/10.1073/pnas.2102512118, 2021.
Hung, H. M., Katrib, Y., and Martin, S. T.:
Products and mechanisms of the reaction of oleic acid with ozone and nitrate radical, J. Phys. Chem. A, 109, 4517–4530, https://doi.org/10.1021/jp0500900, 2005.
King, M. D., Thompson, K. C., and Ward, A. D.:
Laser tweezers raman study of optically trapped aerosol droplets of seawater and oleic acid reacting with ozone: Implications for cloud-droplet properties, J. Am. Chem. Soc., 126, 16710–16711, https://doi.org/10.1021/ja044717o, 2004.
King, M. D., Rennie, A. R., Thompson, K. C., Fisher, F. N., Dong, C. C., Thomas, R. K., Pfrang, C., and Hughes, A. V.:
Oxidation of oleic acid at the air-water interface and its potential effects on cloud critical supersaturations, Phys. Chem. Chem. Phys., 11, 7699–7707, https://doi.org/10.1039/b906517b, 2009.
King, M. D., Jones, S. H., Lucas, C. O. M., Thompson, K. C., Rennie, A. R., Ward, A. D., Marks, A. A., Fisher, F. N., Pfrang, C., Hughes, A. V., and Campbell, R. A.:
The reaction of oleic acid monolayers with gas-phase ozone at the air water interface: The effect of sub-phase viscosity, and inert secondary components, Phys. Chem. Chem. Phys., 22, 28032–28044, https://doi.org/10.1039/d0cp03934a, 2020.
Knopf, D. A., Anthony, L. M., and Bertram, A. K.:
Reactive uptake of O3 by multicomponent and multiphase mixtures containing oleic acid, J. Phys. Chem. A, 109, 5579–5589, https://doi.org/10.1021/jp0512513, 2005.
Lakey, P. S. J., Wisthaler, A., Berkemeier, T., Mikoviny, T., Pöschl, U., and Shiraiwa, M.:
Chemical kinetics of multiphase reactions between ozone and human skin lipids: Implications for indoor air quality and health effects, Indoor Air, 27, 816–828, https://doi.org/10.1111/ina.12360, 2017.
Lakey, P. S. J., Eichler, C. M. A., Wang, C., Little, J. C., and Shiraiwa, M.:
Kinetic multi-layer model of film formation, growth, and chemistry (KM-FILM): Boundary layer processes, multi-layer adsorption, bulk diffusion, and heterogeneous reactions, Indoor Air, 31, ina.12854, https://doi.org/10.1111/ina.12854, 2021.
Lelieveld, S., Wilson, J., Dovrou, E., Mishra, A., Lakey, P. S. J., Shiraiwa, M., Pöschl, U., and Berkemeier, T.:
Hydroxyl Radical Production by Air Pollutants in Epithelial Lining Fluid Governed by Interconversion and Scavenging of Reactive Oxygen Species, Environ. Sci. Technol., 55, 14069–14079, https://doi.org/10.1021/acs.est.1c03875, 2021.
Lyu, X., Huo, Y., Yang, J., Yao, D., Li, K., Lu, H., Zeren, Y., and Guo, H.:
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Short summary
MultilayerPy is a Python-based framework facilitating the creation, running and optimisation of state-of-the-art kinetic multi-layer models of aerosol and film processes. Models can be fit to data with local and global optimisation algorithms along with a statistical sampling algorithm, which quantifies the uncertainty in optimised model parameters. This “modelling study in a box” enables more reproducible and reliable results, with model code and outputs produced in a human-readable way.
MultilayerPy is a Python-based framework facilitating the creation, running and optimisation of...
