Articles | Volume 7, issue 4
Geosci. Model Dev., 7, 1733–1766, 2014
https://doi.org/10.5194/gmd-7-1733-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 7, 1733–1766, 2014
https://doi.org/10.5194/gmd-7-1733-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
20 Aug 2014
Model description paper
| 20 Aug 2014
Development of two-moment cloud microphysics for liquid and ice within the NASA Goddard Earth Observing System Model (GEOS-5)
D. Barahona et al.
Related authors
Ehud Strobach, Andrea Molod, Donifan Barahona, Atanas Trayanov, Dimitris Menemenlis, and Gael Forget
Geosci. Model Dev., 15, 2309–2324, https://doi.org/10.5194/gmd-15-2309-2022, https://doi.org/10.5194/gmd-15-2309-2022, 2022
Short summary
Short summary
The Green's functions methodology offers a systematic, easy-to-implement, computationally cheap, scalable, and extendable method to tune uncertain parameters in models accounting for the dependent response of the model to a change in various parameters. Herein, we successfully show for the first time that long-term errors in earth system models can be considerably reduced using Green's functions methodology. The method can be easily applied to any model containing uncertain parameters.
Huisheng Bian, Eunjee Lee, Randal D. Koster, Donifan Barahona, Mian Chin, Peter R. Colarco, Anton Darmenov, Sarith Mahanama, Michael Manyin, Peter Norris, John Shilling, Hongbin Yu, and Fanwei Zeng
Atmos. Chem. Phys., 21, 14177–14197, https://doi.org/10.5194/acp-21-14177-2021, https://doi.org/10.5194/acp-21-14177-2021, 2021
Short summary
Short summary
The study using the NASA Earth system model shows ~2.6 % increase in burning season gross primary production and ~1.5 % increase in annual net primary production across the Amazon Basin during 2010–2016 due to the change in surface downward direct and diffuse photosynthetically active radiation by biomass burning aerosols. Such an aerosol effect is strongly dependent on the presence of clouds. The cloud fraction at which aerosols switch from stimulating to inhibiting plant growth occurs at ~0.8.
Katherine H. Breen, Donifan Barahona, Tianle Yuan, Huisheng Bian, and Scott C. James
Atmos. Chem. Phys., 21, 7749–7771, https://doi.org/10.5194/acp-21-7749-2021, https://doi.org/10.5194/acp-21-7749-2021, 2021
Short summary
Short summary
Increases in atmospheric aerosols affect the scattering and absorption of solar radiation by altering the macrophysical and microphysical processes of clouds. We analyzed aerosol–cloud interactions in response to degassing events from the Kilauea volcano in 2008 and 2018 by comparing satellite and simulated cloud properties. Results showed a threshold response to overcome meteorological effects that is largely controlled by aerosol concentration, composition, plume height, and ENSO state.
Jie Gong, Xiping Zeng, Dong L. Wu, S. Joseph Munchak, Xiaowen Li, Stefan Kneifel, Davide Ori, Liang Liao, and Donifan Barahona
Atmos. Chem. Phys., 20, 12633–12653, https://doi.org/10.5194/acp-20-12633-2020, https://doi.org/10.5194/acp-20-12633-2020, 2020
Short summary
Short summary
This work provides a novel way of using polarized passive microwave measurements to study the interlinked cloud–convection–precipitation processes. The magnitude of differences between polarized radiances is found linked to ice microphysics (shape, size, orientation and density), mesoscale dynamic and thermodynamic structures, and surface precipitation. We conclude that passive sensors with multiple polarized channel pairs may serve as cheaper and useful substitutes for spaceborne radar sensors.
Donifan Barahona
Atmos. Chem. Phys., 18, 17119–17141, https://doi.org/10.5194/acp-18-17119-2018, https://doi.org/10.5194/acp-18-17119-2018, 2018
Short summary
Short summary
This work develops a model for ice formation mediated by particles immersed within droplets. Ice nucleation is not only enhanced by the modification of the thermodynamic properties of the vicinal water but is also inhibited by decreased water mobility near the particle. The ice nucleation rate is thus determined by competing kinetic and thermodynamic factors during ice formation. A new regime where ice nucleation is mediated mainly by kinetics instead of thermodynamics is discovered.
Sara Bacer, Sylvia C. Sullivan, Vlassis A. Karydis, Donifan Barahona, Martina Krämer, Athanasios Nenes, Holger Tost, Alexandra P. Tsimpidi, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 11, 4021–4041, https://doi.org/10.5194/gmd-11-4021-2018, https://doi.org/10.5194/gmd-11-4021-2018, 2018
Short summary
Short summary
The complexity of ice nucleation mechanisms and aerosol--ice interactions makes their representation still challenging in atmospheric models. We have implemented a comprehensive ice crystal formation parameterization in the global chemistry-climate model EMAC to improve the representation of ice crystal number concentrations. The newly implemented parameterization takes into account processes which were previously neglected by the standard version of the model.
Sylvia C. Sullivan, Ricardo Morales Betancourt, Donifan Barahona, and Athanasios Nenes
Atmos. Chem. Phys., 16, 2611–2629, https://doi.org/10.5194/acp-16-2611-2016, https://doi.org/10.5194/acp-16-2611-2016, 2016
Short summary
Short summary
We use the adjoint model of a cirrus parameterization to quantify sources of crystal variability for various ice-nucleating spectra and output from CAM5.
The sensitivities can be directly linked to nucleation regime and
efficiency of various INP.
The lab-based spectrum calculates much higher INP efficiencies than field-based ones, owing to aerosol surface properties.
The sensitivity to temperature tends to be low, due to the compensating effects of temperature on INP spectrum parameters.
D. Barahona
Atmos. Chem. Phys., 15, 13819–13831, https://doi.org/10.5194/acp-15-13819-2015, https://doi.org/10.5194/acp-15-13819-2015, 2015
Short summary
Short summary
This paper describes the process of the transfer of water molecules between liquid and the ice during the early stages of ice formation. Using concepts of nonreversible thermodynamics, it is shown that the activation energy can be defined in terms of the bulk self-diffusivity of water and the probability of interface transfer. The application of this model to classical nucleation theory shows good agreement of measured nucleation rates with experimental results for temperatures as low as 190K.
D. Barahona
Atmos. Chem. Phys., 14, 7665–7680, https://doi.org/10.5194/acp-14-7665-2014, https://doi.org/10.5194/acp-14-7665-2014, 2014
Y. C. Sud, D. Lee, L. Oreopoulos, D. Barahona, A. Nenes, and M. J. Suarez
Geosci. Model Dev., 6, 57–79, https://doi.org/10.5194/gmd-6-57-2013, https://doi.org/10.5194/gmd-6-57-2013, 2013
Guangyu Li, Elise K. Wilbourn, Zezhen Cheng, Jörg Wieder, Allison Fagerson, Jan Henneberger, Ghislain Motos, Rita Traversi, Sarah D. Brooks, Mauro Mazzola, Swarup China, Athanasios Nenes, Ulrike Lohmann, Naruki Hiranuma, and Zamin A. Kanji
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2023-18, https://doi.org/10.5194/acp-2023-18, 2023
Preprint under review for ACP
Short summary
Short summary
In this work, we present results from an Arctic field campaign (NASCENT) in Ny-Ålesund, Svalbard, on the abundance, variability, physicochemical properties and potential sources of ice-nucleating particles relevant for mixed-phase cloud formation. This work improves the data coverage of Arctic INPs and aerosol properties, allowing for the validation of models predicting cloud microphysical and radiative properties of mixed-phase clouds in the rapidly warming Arctic.
Marios Chatziparaschos, Nikos Daskalakis, Stelios Myriokefalitakis, Nikos Kalivitis, Athanasios Nenes, María Gonçalves Ageitos, Montserrat Costa-Surós, Carlos Pérez García-Pando, Medea Zanoli, Mihalis Vrekoussis, and Maria Kanakidou
Atmos. Chem. Phys., 23, 1785–1801, https://doi.org/10.5194/acp-23-1785-2023, https://doi.org/10.5194/acp-23-1785-2023, 2023
Short summary
Short summary
Ice formation is enabled by ice-nucleating particles (INP) at higher temperatures than homogeneous formation and can profoundly affect the properties of clouds. Our global model results show that K-feldspar is the most important contributor to INP concentrations globally, affecting mid-level mixed-phase clouds. However, quartz can significantly contribute and dominates the lowest and the highest altitudes of dust-derived INP, affecting mainly low-level and high-level mixed-phase clouds.
Stylianos Kakavas, Spyros Pandis, and Athanasios Nenes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-815, https://doi.org/10.5194/acp-2022-815, 2023
Preprint under review for ACP
Short summary
Short summary
Water uptake from organic species in aerosol can affect the partitioning of semi-volatile inorganic compounds, but are not considered in global and chemical transport models. We address this with a version of the PM-CAMx model that considers such organic water effects and use it to carry out year-long aerosol simulations over the continental US. We show that such organic water impacts can have an important impact on dry PM1 levels when RH levels and PM1 concentrations are high.
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
EGUsphere, https://doi.org/10.5194/egusphere-2022-1199, https://doi.org/10.5194/egusphere-2022-1199, 2023
Short summary
Short summary
We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique for its following a standard protocol designed for coordinated experiments of regional models. 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 under rapidly changing super computer systems are illustrated.
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
EGUsphere, https://doi.org/10.5194/egusphere-2022-980, https://doi.org/10.5194/egusphere-2022-980, 2022
Short summary
Short summary
Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth System Models. These updates include the ability to run the scheme on Graphics Processing Units (GPUs) and changes to the numerical description of precipitation, as well as a correction to ice number. There are big improvements in computational performance that can be achieved with GPU acceleration.
Xingying Huang, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda
Geosci. Model Dev., 15, 8135–8151, https://doi.org/10.5194/gmd-15-8135-2022, https://doi.org/10.5194/gmd-15-8135-2022, 2022
Short summary
Short summary
We focus on the recent development of a state-of-the-art storm-resolving global climate model and investigate how this next-generation model performs for precipitation prediction over the western USA. Results show realistic representations of precipitation with significantly enhanced snowpack over complex terrains. The model evaluation advances the unified modeling of large-scale forcing constraints and realistic fine-scale features to advance multi-scale climate predictions and changes.
Amir Yazdani, Satoshi Takahama, John K. Kodros, Marco Paglione, Mauro Masiol, Stefania Squizzato, Kalliopi Florou, Christos Kaltsonoudis, Spiro D. Jorga, Spyros N. Pandis, and Athanasios Nenes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-658, https://doi.org/10.5194/acp-2022-658, 2022
Preprint under review for ACP
Short summary
Short summary
Organic aerosols directly emitted from wood and pellet stove combustion are found to chemically transform (approximately 15–35 % by mass) under daytime aging conditions simulated in an environmental chamber. A new marker for lignin-like compounds is found to degrade at a different rate than previously identified biomass burning markers and can potentially provide indication of aging time in ambient samples.
Emily D. Lenhardt, Lan Gao, Jens Redemann, Feng Xu, Sharon P. Burton, Brian Cairns, Ian Chang, Richard A. Ferrare, Chris A. Hostetler, Pablo E. Saide, Calvin Howes, Yohei Shinozuka, Snorre Stamnes, Mary Kacarab, Amie Dobracki, Jenny Wong, Steffen Freitag, and Athanasios Nenes
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-262, https://doi.org/10.5194/amt-2022-262, 2022
Preprint under review for AMT
Short summary
Short summary
Small atmospheric particles, such as smoke from wildfires or pollutants from human activities, impact cloud properties, and clouds have a strong influence on climate change. To better understand the distributions of these particles, we develop relationships to derive their concentrations from remote sensing measurements from an instrument called a lidar. Our method is reliable for smoke particles, and similar steps can be taken to develop similar relationships for other particle types.
Zhipeng Qu, Alexei Korolev, Jason A. Milbrandt, Ivan Heckman, Yongjie Huang, Greg M. McFarquhar, Hugh Morrison, Mengistu Wolde, and Cuong Nguyen
Atmos. Chem. Phys., 22, 12287–12310, https://doi.org/10.5194/acp-22-12287-2022, https://doi.org/10.5194/acp-22-12287-2022, 2022
Short summary
Short summary
Secondary ice production (SIP) is an important physical phenomenon that results in an increase in the cloud ice particle concentration and can have a significant impact on the evolution of clouds. Here, idealized simulations of a tropical convective system were conducted. Agreement between the simulations and observations highlights the impacts of SIP on the maintenance of tropical convection in nature and the importance of including the modelling of SIP in numerical weather prediction models.
Caroline Dang, Michal Segal-Rozenhaimer, Haochi Che, Lu Zhang, Paola Formenti, Jonathan Taylor, Amie Dobracki, Sara Purdue, Pui-Shan Wong, Athanasios Nenes, Arthur Sedlacek III, Hugh Coe, Jens Redemann, Paquita Zuidema, Steven Howell, and James Haywood
Atmos. Chem. Phys., 22, 9389–9412, https://doi.org/10.5194/acp-22-9389-2022, https://doi.org/10.5194/acp-22-9389-2022, 2022
Short summary
Short summary
Transmission electron microscopy was used to analyze aged African smoke particles and how the smoke interacts with the marine atmosphere. We found that the volatility of organic aerosol increases with biomass burning plume age, that black carbon is often mixed with potassium salts and that the marine atmosphere can incorporate Na and Cl into smoke particles. Marine salts are more processed when mixed with smoke plumes, and there are interesting Cl-rich yet Na-absent marine particles.
Lu Zhang, Michal Segal-Rozenhaimer, Haochi Che, Caroline Dang, Arthur J. Sedlacek III, Ernie R. Lewis, Amie Dobracki, Jenny P. S. Wong, Paola Formenti, Steven G. Howell, and Athanasios Nenes
Atmos. Chem. Phys., 22, 9199–9213, https://doi.org/10.5194/acp-22-9199-2022, https://doi.org/10.5194/acp-22-9199-2022, 2022
Short summary
Short summary
Widespread biomass burning (BB) events occur annually in Africa and contribute ~ 1 / 3 of global BB emissions, which contain a large family of light-absorbing organics, known as brown carbon (BrC), whose absorption of incident radiation is difficult to estimate, leading to large uncertainties in the global radiative forcing estimation. This study quantifies the BrC absorption of aged BB particles and highlights the potential presence of absorbing iron oxides in this climatically important region.
Stelios Myriokefalitakis, Elisa Bergas-Massó, María Gonçalves-Ageitos, Carlos Pérez García-Pando, Twan van Noije, Philippe Le Sager, Akinori Ito, Eleni Athanasopoulou, Athanasios Nenes, Maria Kanakidou, Maarten C. Krol, and Evangelos Gerasopoulos
Geosci. Model Dev., 15, 3079–3120, https://doi.org/10.5194/gmd-15-3079-2022, https://doi.org/10.5194/gmd-15-3079-2022, 2022
Short summary
Short summary
We here describe the implementation of atmospheric multiphase processes in the EC-Earth Earth system model. We provide global budgets of oxalate, sulfate, and iron-containing aerosols, along with an analysis of the links among atmospheric composition, aqueous-phase processes, and aerosol dissolution, supported by comparison to observations. This work is a first step towards an interactive calculation of the deposition of bioavailable atmospheric iron coupled to the model’s ocean component.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
Short summary
Short summary
An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Ehud Strobach, Andrea Molod, Donifan Barahona, Atanas Trayanov, Dimitris Menemenlis, and Gael Forget
Geosci. Model Dev., 15, 2309–2324, https://doi.org/10.5194/gmd-15-2309-2022, https://doi.org/10.5194/gmd-15-2309-2022, 2022
Short summary
Short summary
The Green's functions methodology offers a systematic, easy-to-implement, computationally cheap, scalable, and extendable method to tune uncertain parameters in models accounting for the dependent response of the model to a change in various parameters. Herein, we successfully show for the first time that long-term errors in earth system models can be considerably reduced using Green's functions methodology. The method can be easily applied to any model containing uncertain parameters.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Ming Xue, Hugh Morrison, Jason Milbrandt, Alexei V. Korolev, Yachao Hu, Zhipeng Qu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, and Ivan Heckman
Atmos. Chem. Phys., 22, 2365–2384, https://doi.org/10.5194/acp-22-2365-2022, https://doi.org/10.5194/acp-22-2365-2022, 2022
Short summary
Short summary
Numerous small ice crystals in tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. Previous numerical simulations failed to reproduce this phenomenon and hypothesized that key microphysical processes are still lacking in current models to realistically simulate the phenomenon. This study uses numerical experiments to confirm the dominant role of secondary ice production in the formation of these large numbers of small ice crystals.
Paraskevi Georgakaki, Georgia Sotiropoulou, Étienne Vignon, Anne-Claire Billault-Roux, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 22, 1965–1988, https://doi.org/10.5194/acp-22-1965-2022, https://doi.org/10.5194/acp-22-1965-2022, 2022
Short summary
Short summary
The modelling study focuses on the importance of ice multiplication processes in orographic mixed-phase clouds, which is one of the least understood cloud types in the climate system. We show that the consideration of ice seeding and secondary ice production through ice–ice collisional breakup is essential for correct predictions of precipitation in mountainous terrain, with important implications for radiation processes.
Ka Ming Fung, Colette L. Heald, Jesse H. Kroll, Siyuan Wang, Duseong S. Jo, Andrew Gettelman, Zheng Lu, Xiaohong Liu, Rahul A. Zaveri, Eric C. Apel, Donald R. Blake, Jose-Luis Jimenez, Pedro Campuzano-Jost, Patrick R. Veres, Timothy S. Bates, John E. Shilling, and Maria Zawadowicz
Atmos. Chem. Phys., 22, 1549–1573, https://doi.org/10.5194/acp-22-1549-2022, https://doi.org/10.5194/acp-22-1549-2022, 2022
Short summary
Short summary
Understanding the natural aerosol burden in the preindustrial era is crucial for us to assess how atmospheric aerosols affect the Earth's radiative budgets. Our study explores how a detailed description of dimethyl sulfide (DMS) oxidation (implemented in the Community Atmospheric Model version 6 with chemistry, CAM6-chem) could help us better estimate the present-day and preindustrial concentrations of sulfate and other relevant chemicals, as well as the resulting aerosol radiative impacts.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
Short summary
Short summary
Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Irini Tsiodra, Georgios Grivas, Kalliopi Tavernaraki, Aikaterini Bougiatioti, Maria Apostolaki, Despina Paraskevopoulou, Alexandra Gogou, Constantine Parinos, Konstantina Oikonomou, Maria Tsagkaraki, Pavlos Zarmpas, Athanasios Nenes, and Nikolaos Mihalopoulos
Atmos. Chem. Phys., 21, 17865–17883, https://doi.org/10.5194/acp-21-17865-2021, https://doi.org/10.5194/acp-21-17865-2021, 2021
Short summary
Short summary
We analyze observations from year-long measurements at Athens, Greece. Nighttime wintertime PAH levels are 4 times higher than daytime, and wintertime values are 15 times higher than summertime. Biomass burning aerosol during wintertime pollution events is responsible for these significant wintertime enhancements and accounts for 43 % of the population exposure to PAH carcinogenic risk. Biomass burning poses additional health risks beyond those associated with the high PM levels that develop.
Mária Lbadaoui-Darvas, Satoshi Takahama, and Athanasios Nenes
Atmos. Chem. Phys., 21, 17687–17714, https://doi.org/10.5194/acp-21-17687-2021, https://doi.org/10.5194/acp-21-17687-2021, 2021
Short summary
Short summary
Aerosol–cloud interactions constitute the most uncertain contribution to climate change. The uptake kinetics of water by aerosol is a central process of cloud droplet formation, yet its molecular-scale mechanism is unknown. We use molecular simulations to study this process for phase-separated organic particles. Our results explain the increased cloud condensation activity of such particles and can be generalized over various compositions, thus possibly serving as a basis for future models.
Spiro D. Jorga, Kalliopi Florou, Christos Kaltsonoudis, John K. Kodros, Christina Vasilakopoulou, Manuela Cirtog, Axel Fouqueau, Bénédicte Picquet-Varrault, Athanasios Nenes, and Spyros N. Pandis
Atmos. Chem. Phys., 21, 15337–15349, https://doi.org/10.5194/acp-21-15337-2021, https://doi.org/10.5194/acp-21-15337-2021, 2021
Short summary
Short summary
We test the hypothesis that significant secondary organic aerosol production can take place even during winter nights through the oxidation of the emitted organic vapors by the nitrate radicals produced during the reaction of ozone and nitrogen oxides. Our experiments, using as a starting point the ambient air of an urban area with high biomass burning activity, demonstrate that, even with sunlight, there is 20 %–70 % additional organic aerosol formed in a few hours.
Huisheng Bian, Eunjee Lee, Randal D. Koster, Donifan Barahona, Mian Chin, Peter R. Colarco, Anton Darmenov, Sarith Mahanama, Michael Manyin, Peter Norris, John Shilling, Hongbin Yu, and Fanwei Zeng
Atmos. Chem. Phys., 21, 14177–14197, https://doi.org/10.5194/acp-21-14177-2021, https://doi.org/10.5194/acp-21-14177-2021, 2021
Short summary
Short summary
The study using the NASA Earth system model shows ~2.6 % increase in burning season gross primary production and ~1.5 % increase in annual net primary production across the Amazon Basin during 2010–2016 due to the change in surface downward direct and diffuse photosynthetically active radiation by biomass burning aerosols. Such an aerosol effect is strongly dependent on the presence of clouds. The cloud fraction at which aerosols switch from stimulating to inhibiting plant growth occurs at ~0.8.
Wojciech W. Grabowski and Hugh Morrison
Atmos. Chem. Phys., 21, 13997–14018, https://doi.org/10.5194/acp-21-13997-2021, https://doi.org/10.5194/acp-21-13997-2021, 2021
Short summary
Short summary
The paper provides a discussion of key elements of moist convective dynamics: cloud buoyancy, latent heating, precipitation, and entrainment. The motivation comes from recent discussions concerning differences in convective dynamics in polluted and pristine environments.
Andreas Tilgner, Thomas Schaefer, Becky Alexander, Mary Barth, Jeffrey L. Collett Jr., Kathleen M. Fahey, Athanasios Nenes, Havala O. T. Pye, Hartmut Herrmann, and V. Faye McNeill
Atmos. Chem. Phys., 21, 13483–13536, https://doi.org/10.5194/acp-21-13483-2021, https://doi.org/10.5194/acp-21-13483-2021, 2021
Short summary
Short summary
Feedbacks of acidity and atmospheric multiphase chemistry in deliquesced particles and clouds are crucial for the tropospheric composition, depositions, climate, and human health. This review synthesizes the current scientific knowledge on these feedbacks using both inorganic and organic aqueous-phase chemistry. Finally, this review outlines atmospheric implications and highlights the need for future investigations with respect to reducing emissions of key acid precursors in a changing world.
Paraskevi Georgakaki, Aikaterini Bougiatioti, Jörg Wieder, Claudia Mignani, Fabiola Ramelli, Zamin A. Kanji, Jan Henneberger, Maxime Hervo, Alexis Berne, Ulrike Lohmann, and Athanasios Nenes
Atmos. Chem. Phys., 21, 10993–11012, https://doi.org/10.5194/acp-21-10993-2021, https://doi.org/10.5194/acp-21-10993-2021, 2021
Short summary
Short summary
Aerosol and cloud observations coupled with a droplet activation parameterization was used to investigate the aerosol–cloud droplet link in alpine mixed-phase clouds. Predicted droplet number, Nd, agrees with observations and never exceeds a characteristic “limiting droplet number”, Ndlim, which depends solely on σw. Nd becomes velocity limited when it is within 50 % of Ndlim. Identifying when dynamical changes control Nd variability is central for understanding aerosol–cloud interactions.
Georgia Sotiropoulou, Luisa Ickes, Athanasios Nenes, and Annica M. L. Ekman
Atmos. Chem. Phys., 21, 9741–9760, https://doi.org/10.5194/acp-21-9741-2021, https://doi.org/10.5194/acp-21-9741-2021, 2021
Short summary
Short summary
Mixed-phase clouds are a large source of uncertainty in projections of the Arctic climate. This is partly due to the poor representation of the cloud ice formation processes. Implementing a parameterization for ice multiplication due to mechanical breakup upon collision of two ice particles in a high-resolution model improves cloud ice phase representation; however, cloud liquid remains overestimated.
Andrew Gettelman, Chieh-Chieh Chen, and Charles G. Bardeen
Atmos. Chem. Phys., 21, 9405–9416, https://doi.org/10.5194/acp-21-9405-2021, https://doi.org/10.5194/acp-21-9405-2021, 2021
Short summary
Short summary
The COVID-19 pandemic caused significant economic disruption in 2020 and severely impacted air traffic. We use a climate model to evaluate the effect of the reductions in aviation on climate in 2020. Contrails, in general, warm the planet, and COVID-19-related reductions in contrails cooled the land surface in 2020. The timing of reductions in aviation was important, and this may change how we think about the future effects of contrails.
Katherine H. Breen, Donifan Barahona, Tianle Yuan, Huisheng Bian, and Scott C. James
Atmos. Chem. Phys., 21, 7749–7771, https://doi.org/10.5194/acp-21-7749-2021, https://doi.org/10.5194/acp-21-7749-2021, 2021
Short summary
Short summary
Increases in atmospheric aerosols affect the scattering and absorption of solar radiation by altering the macrophysical and microphysical processes of clouds. We analyzed aerosol–cloud interactions in response to degassing events from the Kilauea volcano in 2008 and 2018 by comparing satellite and simulated cloud properties. Results showed a threshold response to overcome meteorological effects that is largely controlled by aerosol concentration, composition, plume height, and ENSO state.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Xuguang Wang, Hugh Morrison, Alexander Ryzhkov, Yachao Hu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, Jason Milbrandt, Alexei V. Korolev, and Ivan Heckman
Atmos. Chem. Phys., 21, 6919–6944, https://doi.org/10.5194/acp-21-6919-2021, https://doi.org/10.5194/acp-21-6919-2021, 2021
Short summary
Short summary
Numerous small ice crystals in the tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. This study evaluated the numerical models against the airborne observations and investigated the potential cloud processes that could lead to the production of these large numbers of small ice crystals. It is found that key microphysical processes are still lacking or misrepresented in current numerical models to realistically simulate the phenomenon.
Athanasios Nenes, Spyros N. Pandis, Maria Kanakidou, Armistead G. Russell, Shaojie Song, Petros Vasilakos, and Rodney J. Weber
Atmos. Chem. Phys., 21, 6023–6033, https://doi.org/10.5194/acp-21-6023-2021, https://doi.org/10.5194/acp-21-6023-2021, 2021
Short summary
Short summary
Ecosystems and air quality are affected by the dry deposition of inorganic reactive nitrogen (Nr, the sum of ammonium and nitrate). Its large variability is driven by the large difference in deposition velocity of N when in the gas or particle phase. Here we show that aerosol liquid water and acidity, by affecting gas–particle partitioning, modulate the dry deposition velocity of NH3, HNO3, and Nr worldwide. These effects explain the rapid accumulation of nitrate aerosol during haze events.
Yilin Chen, Huizhong Shen, Jennifer Kaiser, Yongtao Hu, Shannon L. Capps, Shunliu Zhao, Amir Hakami, Jhih-Shyang Shih, Gertrude K. Pavur, Matthew D. Turner, Daven K. Henze, Jaroslav Resler, Athanasios Nenes, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Tianfeng Chai, Lieven Clarisse, Pierre-François Coheur, Martin Van Damme, and Armistead G. Russell
Atmos. Chem. Phys., 21, 2067–2082, https://doi.org/10.5194/acp-21-2067-2021, https://doi.org/10.5194/acp-21-2067-2021, 2021
Short summary
Short summary
Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3 emission inventories are viewed as highly uncertain. Here we optimize the NH3 emission estimates in the US using an air quality model and NH3 measurements from the IASI satellite instruments. The optimized NH3 emissions are much higher than the National Emissions Inventory estimates in April. The optimized NH3 emissions improved model performance when evaluated against independent observation.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
Short summary
Short summary
Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Stylianos Kakavas, David Patoulias, Maria Zakoura, Athanasios Nenes, and Spyros N. Pandis
Atmos. Chem. Phys., 21, 799–811, https://doi.org/10.5194/acp-21-799-2021, https://doi.org/10.5194/acp-21-799-2021, 2021
Short summary
Short summary
The dependence of aerosol acidity on particle size, location, and altitude over Europe during a summertime period is investigated. Differences of up to 1–4 pH units are predicted between sub- and supermicron particles in northern and southern Europe. Particles of all sizes become increasingly acidic with altitude (0.5–2.5 pH units decrease over 2.5 km). The size-dependent pH differences carry important implications for pH-sensitive processes in the aerosol.
Georgia Sotiropoulou, Étienne Vignon, Gillian Young, Hugh Morrison, Sebastian J. O'Shea, Thomas Lachlan-Cope, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 21, 755–771, https://doi.org/10.5194/acp-21-755-2021, https://doi.org/10.5194/acp-21-755-2021, 2021
Short summary
Short summary
Summer clouds have a significant impact on the radiation budget of the Antarctic surface and thus on ice-shelf melting. However, these are poorly represented in climate models due to errors in their microphysical structure, including the number of ice crystals that they contain. We show that breakup from ice particle collisions can substantially magnify the ice crystal number concentration with significant implications for surface radiation. This process is currently missing in climate models.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
Short summary
Short summary
Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Ari Laaksonen, Jussi Malila, and Athanasios Nenes
Atmos. Chem. Phys., 20, 13579–13589, https://doi.org/10.5194/acp-20-13579-2020, https://doi.org/10.5194/acp-20-13579-2020, 2020
Short summary
Short summary
Aerosol particles containing black carbon are ubiquitous in the atmosphere and originate from combustion processes. We examine their capability to act as condensation centers for water vapor. We make use of published experimental data sets for different types of black carbon particles, ranging from very pure particles to particles that contain both black carbon and water soluble organic matter, and we show that a recently developed theory reproduces most of the experimental results.
Lanxiadi Chen, Chao Peng, Wenjun Gu, Hanjing Fu, Xing Jian, Huanhuan Zhang, Guohua Zhang, Jianxi Zhu, Xinming Wang, and Mingjin Tang
Atmos. Chem. Phys., 20, 13611–13626, https://doi.org/10.5194/acp-20-13611-2020, https://doi.org/10.5194/acp-20-13611-2020, 2020
Short summary
Short summary
We investigated hygroscopic properties of a number of mineral dust particles in a quantitative manner, via measuring the sample mass at different relative humidities. The robust and comprehensive data obtained would significantly improve our knowledge of hygroscopicity of mineral dust and its impacts on atmospheric chemistry and climate.
Jie Gong, Xiping Zeng, Dong L. Wu, S. Joseph Munchak, Xiaowen Li, Stefan Kneifel, Davide Ori, Liang Liao, and Donifan Barahona
Atmos. Chem. Phys., 20, 12633–12653, https://doi.org/10.5194/acp-20-12633-2020, https://doi.org/10.5194/acp-20-12633-2020, 2020
Short summary
Short summary
This work provides a novel way of using polarized passive microwave measurements to study the interlinked cloud–convection–precipitation processes. The magnitude of differences between polarized radiances is found linked to ice microphysics (shape, size, orientation and density), mesoscale dynamic and thermodynamic structures, and surface precipitation. We conclude that passive sensors with multiple polarized channel pairs may serve as cheaper and useful substitutes for spaceborne radar sensors.
Aikaterini Bougiatioti, Athanasios Nenes, Jack J. Lin, Charles A. Brock, Joost A. de Gouw, Jin Liao, Ann M. Middlebrook, and André Welti
Atmos. Chem. Phys., 20, 12163–12176, https://doi.org/10.5194/acp-20-12163-2020, https://doi.org/10.5194/acp-20-12163-2020, 2020
Short summary
Short summary
The number concentration of droplets in clouds in the summertime in the southeastern United States is influenced by aerosol variations but limited by the strong competition for supersaturated water vapor. Concurrent variations in vertical velocity magnify the response of cloud droplet number to aerosol increases by up to a factor of 5. Omitting the covariance of vertical velocity with aerosol number may therefore bias estimates of the cloud albedo effect from aerosols.
Ifayoyinsola Ibikunle, Andreas Beyersdorf, Pedro Campuzano-Jost, Chelsea Corr, John D. Crounse, Jack Dibb, Glenn Diskin, Greg Huey, Jose-Luis Jimenez, Michelle J. Kim, Benjamin A. Nault, Eric Scheuer, Alex Teng, Paul O. Wennberg, Bruce Anderson, James Crawford, Rodney Weber, and Athanasios Nenes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-501, https://doi.org/10.5194/acp-2020-501, 2020
Publication in ACP not foreseen
Short summary
Short summary
Analysis of observations over South Korea during the NASA/NIER
KORUS-AQ field campaign show that aerosol is fairly acidic (mean pH 2.43 ± 0.68). Aerosol formation is always sensitive to HNO3 levels, especially in highly polluted regions, while it is only exclusively sensitive to NH3 in some rural/remote regions. Nitrate levels accumulate because dry deposition velocity is low. HNO3 reductions achieved by NOx controls can be the most effective PM reduction strategy for all conditions observed.
Shunliu Zhao, Matthew G. Russell, Amir Hakami, Shannon L. Capps, Matthew D. Turner, Daven K. Henze, Peter B. Percell, Jaroslav Resler, Huizhong Shen, Armistead G. Russell, Athanasios Nenes, Amanda J. Pappin, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Charles O. Stanier, and Tianfeng Chai
Geosci. Model Dev., 13, 2925–2944, https://doi.org/10.5194/gmd-13-2925-2020, https://doi.org/10.5194/gmd-13-2925-2020, 2020
Havala O. T. Pye, Athanasios Nenes, Becky Alexander, Andrew P. Ault, Mary C. Barth, Simon L. Clegg, Jeffrey L. Collett Jr., Kathleen M. Fahey, Christopher J. Hennigan, Hartmut Herrmann, Maria Kanakidou, James T. Kelly, I-Ting Ku, V. Faye McNeill, Nicole Riemer, Thomas Schaefer, Guoliang Shi, Andreas Tilgner, John T. Walker, Tao Wang, Rodney Weber, Jia Xing, Rahul A. Zaveri, and Andreas Zuend
Atmos. Chem. Phys., 20, 4809–4888, https://doi.org/10.5194/acp-20-4809-2020, https://doi.org/10.5194/acp-20-4809-2020, 2020
Short summary
Short summary
Acid rain is recognized for its impacts on human health and ecosystems, and programs to mitigate these effects have had implications for atmospheric acidity. Historical measurements indicate that cloud and fog droplet acidity has changed in recent decades in response to controls on emissions from human activity, while the limited trend data for suspended particles indicate acidity may be relatively constant. This review synthesizes knowledge on the acidity of atmospheric particles and clouds.
Athanasios Nenes, Spyros N. Pandis, Rodney J. Weber, and Armistead Russell
Atmos. Chem. Phys., 20, 3249–3258, https://doi.org/10.5194/acp-20-3249-2020, https://doi.org/10.5194/acp-20-3249-2020, 2020
Short summary
Short summary
We show that aerosol acidity (pH) and liquid water content naturally emerge as previously ignored parameters that drive particulate matter formation in the atmosphere, and its sensitivity to emissions of ammonia and nitric acid. The simple framework presented is easily applied to ambient measurements or model output, and it provides the
chemical regimeof PM sensitivity to ammonia and nitric acid availability.
Mary Kacarab, K. Lee Thornhill, Amie Dobracki, Steven G. Howell, Joseph R. O'Brien, Steffen Freitag, Michael R. Poellot, Robert Wood, Paquita Zuidema, Jens Redemann, and Athanasios Nenes
Atmos. Chem. Phys., 20, 3029–3040, https://doi.org/10.5194/acp-20-3029-2020, https://doi.org/10.5194/acp-20-3029-2020, 2020
Short summary
Short summary
We find that extensive biomass burning aerosol plumes from southern Africa can profoundly influence clouds in the southeastern Atlantic. Concurrent variations in vertical velocity, however, are found to magnify the relationship between boundary layer aerosol and the cloud droplet number. Neglecting these covariances may strongly bias the sign and magnitude of aerosol impacts on the cloud droplet number.
Arnaldo Negron, Natasha DeLeon-Rodriguez, Samantha M. Waters, Luke D. Ziemba, Bruce Anderson, Michael Bergin, Konstantinos T. Konstantinidis, and Athanasios Nenes
Atmos. Chem. Phys., 20, 1817–1838, https://doi.org/10.5194/acp-20-1817-2020, https://doi.org/10.5194/acp-20-1817-2020, 2020
Short summary
Short summary
Airborne biological particles impact human health, cloud formation, and ecosystems, but few techniques are available to characterize their atmospheric abundance. Combining a newly developed high-volume sampling/flow cytometry technique together with an laser-induced fluorescence instrument, we detect a highly dynamic bioaerosol community over urban Atlanta, composed of pollen, fungi, and bacteria with low and high nucleic acid content.
Georgia Sotiropoulou, Sylvia Sullivan, Julien Savre, Gary Lloyd, Thomas Lachlan-Cope, Annica M. L. Ekman, and Athanasios Nenes
Atmos. Chem. Phys., 20, 1301–1316, https://doi.org/10.5194/acp-20-1301-2020, https://doi.org/10.5194/acp-20-1301-2020, 2020
Short summary
Short summary
Arctic clouds constitute a large source of uncertainty in predictions of future climate. Observations indicate that the number concentration of cloud ice crystals exceeds the concentration of aerosols that can act as ice-nucleating particles (INPs). We show that ice multiplication due to mechanical break-up upon collisions between the few primary ice crystals (formed from INPs) can explain the discrepancy. Including a description of the process in climate models can improve cloud representation.
Edward Gryspeerdt, Johannes Mülmenstädt, Andrew Gettelman, Florent F. Malavelle, Hugh Morrison, David Neubauer, Daniel G. Partridge, Philip Stier, Toshihiko Takemura, Hailong Wang, Minghuai Wang, and Kai Zhang
Atmos. Chem. Phys., 20, 613–623, https://doi.org/10.5194/acp-20-613-2020, https://doi.org/10.5194/acp-20-613-2020, 2020
Short summary
Short summary
Aerosol radiative forcing is a key uncertainty in our understanding of the human forcing of the climate, with much of this uncertainty coming from aerosol impacts on clouds. Observation-based estimates of the radiative forcing are typically smaller than those from global models, but it is not clear if they are more reliable. This work shows how the forcing components in global climate models can be identified, highlighting similarities between the two methods and areas for future investigation.
Michael A. Battaglia Jr., Rodney J. Weber, Athanasios Nenes, and Christopher J. Hennigan
Atmos. Chem. Phys., 19, 14607–14620, https://doi.org/10.5194/acp-19-14607-2019, https://doi.org/10.5194/acp-19-14607-2019, 2019
Short summary
Short summary
The effects of water-soluble organic carbon (WSOC) on aerosol pH were characterized for aqueous-phase particles containing a mixture of inorganics and organics. The ISORROPIA-II and E-AIM models were used in conjunction with AIOMFAC to quantify the effect of organics on aerosol pH through (1) changes to the aerosol liquid water content and (2) changes to the hydrogen ion activity coefficient. The study included both organic acids and nonacids, at RH levels ranging from 70 to 90 %.
Eleni Marinou, Matthias Tesche, Athanasios Nenes, Albert Ansmann, Jann Schrod, Dimitra Mamali, Alexandra Tsekeri, Michael Pikridas, Holger Baars, Ronny Engelmann, Kalliopi-Artemis Voudouri, Stavros Solomos, Jean Sciare, Silke Groß, Florian Ewald, and Vassilis Amiridis
Atmos. Chem. Phys., 19, 11315–11342, https://doi.org/10.5194/acp-19-11315-2019, https://doi.org/10.5194/acp-19-11315-2019, 2019
Short summary
Short summary
We assess the feasibility of ground-based and spaceborne lidars to retrieve profiles of cloud-relevant aerosol concentrations and ice-nucleating particles. The retrieved profiles are in good agreement with airborne in situ measurements. Our methodology will be applied to satellite observations in the future so as to provide a global 3D product of cloud-relevant properties.
Lei Lin, Andrew Gettelman, Yangyang Xu, Chenglai Wu, Zhili Wang, Nan Rosenbloom, Susan C. Bates, and Wenjie Dong
Geosci. Model Dev., 12, 3773–3793, https://doi.org/10.5194/gmd-12-3773-2019, https://doi.org/10.5194/gmd-12-3773-2019, 2019
Short summary
Short summary
Here we evaluate the performance of the Community Atmosphere Model version 6 (CAM6) released in 2018, with the default 1º horizontal resolution and a higher-resolution simulation (approximately 0.25º), against various precipitation observational datasets over Asia. With the prognostic treatment of precipitation processes (which is missing in CAM5) and the new microphysics module, CAM6 is able to better simulate climatological mean and extreme precipitation over Asia.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617, https://doi.org/10.5194/acp-19-8591-2019, https://doi.org/10.5194/acp-19-8591-2019, 2019
Short summary
Short summary
Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Jenny P. S. Wong, Maria Tsagkaraki, Irini Tsiodra, Nikolaos Mihalopoulos, Kalliopi Violaki, Maria Kanakidou, Jean Sciare, Athanasios Nenes, and Rodney J. Weber
Atmos. Chem. Phys., 19, 7319–7334, https://doi.org/10.5194/acp-19-7319-2019, https://doi.org/10.5194/acp-19-7319-2019, 2019
Short summary
Short summary
Biomass burning is a major source of light-absorbing organic species in atmospheric aerosols, and it can play an important role in climate and atmospheric chemistry. Through a combination of laboratory experiments and field observations, this work demonstrated that the light absorption properties of aged biomass burning organic aerosols are dominated by high-molecular-weight compounds. In addition, we found that total hydrated sugars may be a robust tracer for aged biomass burning aerosols.
Panayiotis Kalkavouras, Aikaterini Bougiatioti, Nikos Kalivitis, Iasonas Stavroulas, Maria Tombrou, Athanasios Nenes, and Nikolaos Mihalopoulos
Atmos. Chem. Phys., 19, 6185–6203, https://doi.org/10.5194/acp-19-6185-2019, https://doi.org/10.5194/acp-19-6185-2019, 2019
Short summary
Short summary
We study how new particle formation (NPF) events affect clouds throughout the year at a ground site in the E Mediterranean. Using a new tools and evaluation metrics, NPF is found to affect only evening and nocturnal clouds by modestly increasing droplet number by 7 to 12 %. A conventional analysis based on CCN concentration at prescribed supersaturation levels or aerosol size can considerably bias the perceived influence of NPF events on regional clouds, the hydrological cycle, and climate.
Edward Gryspeerdt, Tom Goren, Odran Sourdeval, Johannes Quaas, Johannes Mülmenstädt, Sudhakar Dipu, Claudia Unglaub, Andrew Gettelman, and Matthew Christensen
Atmos. Chem. Phys., 19, 5331–5347, https://doi.org/10.5194/acp-19-5331-2019, https://doi.org/10.5194/acp-19-5331-2019, 2019
Short summary
Short summary
The liquid water path (LWP) is the strongest control on cloud albedo, such that a small change in LWP can have a large radiative impact. By changing the droplet number concentration (Nd) aerosols may be able to change the LWP, but the sign and magnitude of the effect is unclear. This work uses satellite data to investigate the relationship between Nd and LWP at a global scale and in response to large aerosol perturbations, suggesting that a strong decrease in LWP at high Nd may be overestimated.
Nønne L. Prisle, Jack J. Lin, Sara Purdue, Haisheng Lin, J. Carson Meredith, and Athanasios Nenes
Atmos. Chem. Phys., 19, 4741–4761, https://doi.org/10.5194/acp-19-4741-2019, https://doi.org/10.5194/acp-19-4741-2019, 2019
Short summary
Short summary
We measure surface activity and cloud-forming potential of pollenkitt, an organic mixture coating pollen grains. Cloud droplet formation is affected through both surface tension and bulk depletion, with a consistent particle size-dependent signature. We observe nonideal solution effects in pollenkitt mixtures with ammonium sulfate salt. Our results suggest sensitivity of general water interactions, including cloud formation by pollen and their fragments, to both atmospheric humidity and aging.
Joseph A. Finlon, Greg M. McFarquhar, Stephen W. Nesbitt, Robert M. Rauber, Hugh Morrison, Wei Wu, and Pengfei Zhang
Atmos. Chem. Phys., 19, 3621–3643, https://doi.org/10.5194/acp-19-3621-2019, https://doi.org/10.5194/acp-19-3621-2019, 2019
Short summary
Short summary
A new approach describing the relationship between ice crystal mass (m) and dimension (D) is derived, characterizing it as a set of
equally realizableparameters based on the natural variability in cloud conditions observed by aircraft over the Great Plains. Results from this approach address shortcomings of microphysical parameterization schemes and remote sensing retrievals that employ a single m–D relation for a given ice species or environment.
Hongyu Guo, Athanasios Nenes, and Rodney J. Weber
Atmos. Chem. Phys., 18, 17307–17323, https://doi.org/10.5194/acp-18-17307-2018, https://doi.org/10.5194/acp-18-17307-2018, 2018
Short summary
Short summary
Overprediction of fine-particle ammonium-sulfate molar ratios (R) by thermodynamic models is suggested as evidence for organic aerosol limiting the condensation of ammonia onto particles, with significant impacts on aerosol chemistry. We find that the effects of small amounts of salt and dust, combined with measurement artifacts, explain the discrepancy in R. These results are highly insensitive to mixing state. This means that aerosol predictions are much more robust than thought before.
Donifan Barahona
Atmos. Chem. Phys., 18, 17119–17141, https://doi.org/10.5194/acp-18-17119-2018, https://doi.org/10.5194/acp-18-17119-2018, 2018
Short summary
Short summary
This work develops a model for ice formation mediated by particles immersed within droplets. Ice nucleation is not only enhanced by the modification of the thermodynamic properties of the vicinal water but is also inhibited by decreased water mobility near the particle. The ice nucleation rate is thus determined by competing kinetic and thermodynamic factors during ice formation. A new regime where ice nucleation is mediated mainly by kinetics instead of thermodynamics is discovered.
Sylvia C. Sullivan, Christian Barthlott, Jonathan Crosier, Ilya Zhukov, Athanasios Nenes, and Corinna Hoose
Atmos. Chem. Phys., 18, 16461–16480, https://doi.org/10.5194/acp-18-16461-2018, https://doi.org/10.5194/acp-18-16461-2018, 2018
Short summary
Short summary
Ice crystal formation in clouds can occur via thermodynamic nucleation, but also via mechanical collisions between pre-existing crystals or co-existing droplets. When descriptions of this mechanical ice generation are implemented into the COSMO weather model, we find that the contributions to crystal number from thermodynamic and mechanical processes are of the same order. Mechanical ice generation also intensifies differences in precipitation intensity between dynamic and quiescent regions.
Stelios Myriokefalitakis, Akinori Ito, Maria Kanakidou, Athanasios Nenes, Maarten C. Krol, Natalie M. Mahowald, Rachel A. Scanza, Douglas S. Hamilton, Matthew S. Johnson, Nicholas Meskhidze, Jasper F. Kok, Cecile Guieu, Alex R. Baker, Timothy D. Jickells, Manmohan M. Sarin, Srinivas Bikkina, Rachel Shelley, Andrew Bowie, Morgane M. G. Perron, and Robert A. Duce
Biogeosciences, 15, 6659–6684, https://doi.org/10.5194/bg-15-6659-2018, https://doi.org/10.5194/bg-15-6659-2018, 2018
Short summary
Short summary
The first atmospheric iron (Fe) deposition model intercomparison is presented in this study, as a result of the deliberations of the United Nations Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP; http://www.gesamp.org/) Working Group 38. We conclude that model diversity over remote oceans reflects uncertainty in the Fe content parameterizations of dust aerosols, combustion aerosol emissions and the size distribution of transported aerosol Fe.
Sara Bacer, Sylvia C. Sullivan, Vlassis A. Karydis, Donifan Barahona, Martina Krämer, Athanasios Nenes, Holger Tost, Alexandra P. Tsimpidi, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 11, 4021–4041, https://doi.org/10.5194/gmd-11-4021-2018, https://doi.org/10.5194/gmd-11-4021-2018, 2018
Short summary
Short summary
The complexity of ice nucleation mechanisms and aerosol--ice interactions makes their representation still challenging in atmospheric models. We have implemented a comprehensive ice crystal formation parameterization in the global chemistry-climate model EMAC to improve the representation of ice crystal number concentrations. The newly implemented parameterization takes into account processes which were previously neglected by the standard version of the model.
Petros Vasilakos, Armistead Russell, Rodney Weber, and Athanasios Nenes
Atmos. Chem. Phys., 18, 12765–12775, https://doi.org/10.5194/acp-18-12765-2018, https://doi.org/10.5194/acp-18-12765-2018, 2018
Short summary
Short summary
In this work, we investigated the role of emission reductions on aerosol acidity and particulate nitrate. We found that models exhibit positive biases in pH predictions, attributed to very high levels of crustal elements (Mg, Ca, K) in model simulations, which in turn led to an increasing aerosol pH trend over the past decade and allowed nitrate to become an important component of aerosol, which is inconsistent with the measurements, highlighting the importance of accurate pH prediction.
Hongyu Guo, Rene Otjes, Patrick Schlag, Astrid Kiendler-Scharr, Athanasios Nenes, and Rodney J. Weber
Atmos. Chem. Phys., 18, 12241–12256, https://doi.org/10.5194/acp-18-12241-2018, https://doi.org/10.5194/acp-18-12241-2018, 2018
Short summary
Short summary
Reduction in ammonia has been proposed as a way to lower fine particle mass and improve air quality, but gas-phase ammonia is linked to agricultural productivity. We assess the feasibility of ammonia control at a variety of locations through an aerosol thermodynamic analysis. We show that aerosol response to ammonia control is highly nonlinear and only becomes effective when ambient particle pH drops below approximately 3. Particle pH is a relevant aerosol air quality parameter.
Theodora Nah, Hongyu Guo, Amy P. Sullivan, Yunle Chen, David J. Tanner, Athanasios Nenes, Armistead Russell, Nga Lee Ng, L. Gregory Huey, and Rodney J. Weber
Atmos. Chem. Phys., 18, 11471–11491, https://doi.org/10.5194/acp-18-11471-2018, https://doi.org/10.5194/acp-18-11471-2018, 2018
Short summary
Short summary
We present measurements from a field study conducted in an agriculturally intensive region in the southeastern US during the fall of 2016 to investigate how NH3 affects particle acidity and SOA formation via gas–particle partitioning of semi-volatile organic acids. For this study, higher NH3 concentrations relative to what has been measured in the region in previous studies had minor effects on PM1 organic acids and their influence on the overall organic aerosol and PM1 mass concentrations.
Evangelia Kostenidou, Eleni Karnezi, James R. Hite Jr., Aikaterini Bougiatioti, Kate Cerully, Lu Xu, Nga L. Ng, Athanasios Nenes, and Spyros N. Pandis
Atmos. Chem. Phys., 18, 5799–5819, https://doi.org/10.5194/acp-18-5799-2018, https://doi.org/10.5194/acp-18-5799-2018, 2018
Short summary
Short summary
The volatility distribution of organic aerosol (OA) and its sources during the Southern Oxidant and Aerosol Study (SOAS) was estimated. The volatility distribution of all components covered a wide range including both semi-volatile and low-volatility components. The oxygen content of the factors can be combined with their estimated volatility and hygroscopicity to provide a better view of their physical properties.
Julia Schmale, Silvia Henning, Stefano Decesari, Bas Henzing, Helmi Keskinen, Karine Sellegri, Jurgita Ovadnevaite, Mira L. Pöhlker, Joel Brito, Aikaterini Bougiatioti, Adam Kristensson, Nikos Kalivitis, Iasonas Stavroulas, Samara Carbone, Anne Jefferson, Minsu Park, Patrick Schlag, Yoko Iwamoto, Pasi Aalto, Mikko Äijälä, Nicolas Bukowiecki, Mikael Ehn, Göran Frank, Roman Fröhlich, Arnoud Frumau, Erik Herrmann, Hartmut Herrmann, Rupert Holzinger, Gerard Kos, Markku Kulmala, Nikolaos Mihalopoulos, Athanasios Nenes, Colin O'Dowd, Tuukka Petäjä, David Picard, Christopher Pöhlker, Ulrich Pöschl, Laurent Poulain, André Stephan Henry Prévôt, Erik Swietlicki, Meinrat O. Andreae, Paulo Artaxo, Alfred Wiedensohler, John Ogren, Atsushi Matsuki, Seong Soo Yum, Frank Stratmann, Urs Baltensperger, and Martin Gysel
Atmos. Chem. Phys., 18, 2853–2881, https://doi.org/10.5194/acp-18-2853-2018, https://doi.org/10.5194/acp-18-2853-2018, 2018
Short summary
Short summary
Collocated long-term observations of cloud condensation nuclei (CCN) number concentrations, particle number size distributions and chemical composition from 12 sites are synthesized. Observations cover coastal environments, the Arctic, the Mediterranean, the boreal and rain forest, high alpine and continental background sites, and Monsoon-influenced areas. We interpret regional and seasonal variability. CCN concentrations are predicted with the κ–Köhler model and compared to the measurements.
Sylvia C. Sullivan, Corinna Hoose, Alexei Kiselev, Thomas Leisner, and Athanasios Nenes
Atmos. Chem. Phys., 18, 1593–1610, https://doi.org/10.5194/acp-18-1593-2018, https://doi.org/10.5194/acp-18-1593-2018, 2018
Short summary
Short summary
Ice multiplication (IM) processes can have a profound impact on cloud and precipitation development but are poorly understood. Here we study whether a lower limit of ice nuclei exists to initiate IM. The lower limit is found to be extremely low (0.01 per liter or less). A counterintuitive but profound conclusion thus emerges: IM requires cloud formation around a thermodynamic
sweet spotand is sensitive to fluctuations in cloud condensation nuclei concentration alone.
Peter A. Bogenschutz, Andrew Gettelman, Cecile Hannay, Vincent E. Larson, Richard B. Neale, Cheryl Craig, and Chih-Chieh Chen
Geosci. Model Dev., 11, 235–255, https://doi.org/10.5194/gmd-11-235-2018, https://doi.org/10.5194/gmd-11-235-2018, 2018
Short summary
Short summary
This paper compares results of developmental versions of a widely used climate model. The simulations only differ in the choice of how to model the sub-grid-scale physics in the atmospheric model. This work is novel because it is the first time that a particular physics option has been tested in a fully coupled climate model. Here, we demonstrate that this physics option has the ability to produce credible coupled climate simulations, with improved metrics in certain fields.
Bethan White, Edward Gryspeerdt, Philip Stier, Hugh Morrison, Gregory Thompson, and Zak Kipling
Atmos. Chem. Phys., 17, 12145–12175, https://doi.org/10.5194/acp-17-12145-2017, https://doi.org/10.5194/acp-17-12145-2017, 2017
Short summary
Short summary
Aerosols influence cloud and precipitation by modifying cloud droplet number concentrations (CDNCs). We simulate three different types of convective cloud using two different cloud microphysics parameterisations. The simulated cloud and precipitation depends much more strongly on the choice of microphysics scheme than on CDNC. The uncertainty differs between types of convection. Our results highlight a large uncertainty in cloud and precipitation responses to aerosol in current models.
Khairunnisa Yahya, Timothy Glotfelty, Kai Wang, Yang Zhang, and Athanasios Nenes
Geosci. Model Dev., 10, 2333–2363, https://doi.org/10.5194/gmd-10-2333-2017, https://doi.org/10.5194/gmd-10-2333-2017, 2017
Petros Vasilakos, Yong-Ηa Kim, Jeffrey R. Pierce, Sotira Yiacoumi, Costas Tsouris, and Athanasios Nenes
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-96, https://doi.org/10.5194/gmd-2017-96, 2017
Revised manuscript not accepted
Short summary
Short summary
Radioactive charging can significantly impact the way radioactive aerosols behave, and as a result their lifetime, but such effects are neglected in predictive model studies of radioactive plumes. We extend a well-established model that simulates the evolution of atmospheric particulate matter to account for radioactive charging effects in an accurate and computationally efficient way. It is shown that radioactivity can strongly impact the deposition patterns of aerosol.
Hongyu Guo, Jiumeng Liu, Karl D. Froyd, James M. Roberts, Patrick R. Veres, Patrick L. Hayes, Jose L. Jimenez, Athanasios Nenes, and Rodney J. Weber
Atmos. Chem. Phys., 17, 5703–5719, https://doi.org/10.5194/acp-17-5703-2017, https://doi.org/10.5194/acp-17-5703-2017, 2017
Short summary
Short summary
Fine particle pH is linked to many environmental impacts by affecting particle concentration and composition. Predicted Pasadena, CA (CalNex campaign), PM1 pH is 1.9 and PM2.5 pH 2.7, the latter higher due to sea salts. The model predicted gas–particle partitionings of HNO3–NO3−, NH3–NH4+, and HCl–Cl− are in good agreement, verifying the model predictions. A summary of contrasting locations in the US and eastern Mediterranean shows fine particles are generally highly acidic, with pH below 3.
Vlassis A. Karydis, Alexandra P. Tsimpidi, Sara Bacer, Andrea Pozzer, Athanasios Nenes, and Jos Lelieveld
Atmos. Chem. Phys., 17, 5601–5621, https://doi.org/10.5194/acp-17-5601-2017, https://doi.org/10.5194/acp-17-5601-2017, 2017
Short summary
Short summary
The importance of mineral dust for cloud droplet formation is studied by considering the adsorption activation of insoluble dust particles and the thermodynamic interactions between mineral cations and inorganic anions. This study demonstrates that a comprehensive treatment of the CCN activity of mineral dust and its chemical and thermodynamic interactions with inorganic species by chemistry climate models is important to realistically account for aerosol–chemistry–cloud–climate interaction.
Chenglai Wu, Xiaohong Liu, Minghui Diao, Kai Zhang, Andrew Gettelman, Zheng Lu, Joyce E. Penner, and Zhaohui Lin
Atmos. Chem. Phys., 17, 4731–4749, https://doi.org/10.5194/acp-17-4731-2017, https://doi.org/10.5194/acp-17-4731-2017, 2017
Short summary
Short summary
This study utilizes a novel approach to directly compare the CAM5-simulated cloud macro- and microphysics with the collocated HIPPO observations for the period of 2009 to 2011. The model cannot capture the large spatial variabilities of observed RH, which is responsible for much of the model missing low-level warm clouds. A large portion of the RH bias results from the discrepancy in water vapor. The model underestimates the observed number concentration and ice water content.
Andrew Gettelman, Chih-Chieh Chen, Mark Z. Jacobson, Mary A. Cameron, Donald J. Wuebbles, and Arezoo Khodayari
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-218, https://doi.org/10.5194/acp-2017-218, 2017
Revised manuscript not accepted
Short summary
Short summary
Aviation emissions create several impacts on climate. Condensation trails (contrails) are aviation produced cirrus clouds. Aircraft also emit aerosols, including soot (black carbon) and sulfate. Analyses of the climate effects of 2050 aviation emissions have been conducted with two coupled Chemistry Climate Models (CCMs) including experiments with coupled ocean models.
Alexandra Tsekeri, Vassilis Amiridis, Franco Marenco, Athanasios Nenes, Eleni Marinou, Stavros Solomos, Phil Rosenberg, Jamie Trembath, Graeme J. Nott, James Allan, Michael Le Breton, Asan Bacak, Hugh Coe, Carl Percival, and Nikolaos Mihalopoulos
Atmos. Meas. Tech., 10, 83–107, https://doi.org/10.5194/amt-10-83-2017, https://doi.org/10.5194/amt-10-83-2017, 2017
Short summary
Short summary
The In situ/Remote sensing aerosol Retrieval Algorithm (IRRA) provides vertical profiles of aerosol optical, microphysical and hygroscopic properties from airborne in situ and remote sensing measurements. The algorithm is highly advantageous for aerosol characterization in humid conditions, employing the ISORROPIA II model for acquiring the particle hygroscopic growth. IRRA can find valuable applications in aerosol–cloud interaction schemes and in validation of active space-borne sensors.
Havala O. T. Pye, Benjamin N. Murphy, Lu Xu, Nga L. Ng, Annmarie G. Carlton, Hongyu Guo, Rodney Weber, Petros Vasilakos, K. Wyat Appel, Sri Hapsari Budisulistiorini, Jason D. Surratt, Athanasios Nenes, Weiwei Hu, Jose L. Jimenez, Gabriel Isaacman-VanWertz, Pawel K. Misztal, and Allen H. Goldstein
Atmos. Chem. Phys., 17, 343–369, https://doi.org/10.5194/acp-17-343-2017, https://doi.org/10.5194/acp-17-343-2017, 2017
Short summary
Short summary
We use a chemical transport model to examine how organic compounds in the atmosphere interact with water present in particles. Organic compounds themselves lead to water uptake, and organic compounds interact with water associated with inorganic compounds in the rural southeast atmosphere. Including interactions of organic compounds with water requires a treatment of nonideality to more accurately represent aerosol observations during the Southern Oxidant and Aerosol Study (SOAS) 2013.
Panayiotis Kalkavouras, Elissavet Bossioli, Spiros Bezantakos, Aikaterini Bougiatioti, Nikos Kalivitis, Iasonas Stavroulas, Giorgos Kouvarakis, Anna P. Protonotariou, Aggeliki Dandou, George Biskos, Nikolaos Mihalopoulos, Athanasios Nenes, and Maria Tombrou
Atmos. Chem. Phys., 17, 175–192, https://doi.org/10.5194/acp-17-175-2017, https://doi.org/10.5194/acp-17-175-2017, 2017
Short summary
Short summary
Concentrations of chemically and size-resolved submicron aerosol particles along with concentrations of gases and meteorological variables were measured at Santorini and Finokalia (central and southern Aegean Sea) during the Etesians. Particle nucleation bursts were recorded. The NPF can double CCN number (at 0.1 % supersaturation), but the resulting strong competition for water vapor in cloudy updrafts decreases maximum supersaturation by 14 % and augments the potential droplet number by 12 %.
Stelios Myriokefalitakis, Athanasios Nenes, Alex R. Baker, Nikolaos Mihalopoulos, and Maria Kanakidou
Biogeosciences, 13, 6519–6543, https://doi.org/10.5194/bg-13-6519-2016, https://doi.org/10.5194/bg-13-6519-2016, 2016
Short summary
Short summary
The global atmospheric cycle of P is simulated accounting for natural and anthropogenic sources, acid dissolution of dust aerosol and changes in atmospheric acidity. Simulations show that P-containing dust dissolution flux may have increased in the last 150 years but is expected to decrease in the future, and biological particles are important carriers of bioavailable P to the ocean. These insights to the P cycle have important implications for marine ecosystem responses to climate change.
Carsten Warneke, Michael Trainer, Joost A. de Gouw, David D. Parrish, David W. Fahey, A. R. Ravishankara, Ann M. Middlebrook, Charles A. Brock, James M. Roberts, Steven S. Brown, Jonathan A. Neuman, Brian M. Lerner, Daniel Lack, Daniel Law, Gerhard Hübler, Iliana Pollack, Steven Sjostedt, Thomas B. Ryerson, Jessica B. Gilman, Jin Liao, John Holloway, Jeff Peischl, John B. Nowak, Kenneth C. Aikin, Kyung-Eun Min, Rebecca A. Washenfelder, Martin G. Graus, Mathew Richardson, Milos Z. Markovic, Nick L. Wagner, André Welti, Patrick R. Veres, Peter Edwards, Joshua P. Schwarz, Timothy Gordon, William P. Dube, Stuart A. McKeen, Jerome Brioude, Ravan Ahmadov, Aikaterini Bougiatioti, Jack J. Lin, Athanasios Nenes, Glenn M. Wolfe, Thomas F. Hanisco, Ben H. Lee, Felipe D. Lopez-Hilfiker, Joel A. Thornton, Frank N. Keutsch, Jennifer Kaiser, Jingqiu Mao, and Courtney D. Hatch
Atmos. Meas. Tech., 9, 3063–3093, https://doi.org/10.5194/amt-9-3063-2016, https://doi.org/10.5194/amt-9-3063-2016, 2016
Short summary
Short summary
In this paper we describe the experimental approach, the science goals and early results of the NOAA SENEX campaign, which was focused on studying the interactions between biogenic and anthropogenic emissions to form secondary pollutants.
During SENEX, the NOAA WP-3D aircraft conducted 20 research flights between 27 May and 10 July 2013 based out of Smyrna, TN. The SENEX flights included day- and nighttime flights in the Southeast as well as flights over areas with intense shale gas extraction.
Aikaterini Bougiatioti, Spiros Bezantakos, Iasonas Stavroulas, Nikos Kalivitis, Panagiotis Kokkalis, George Biskos, Nikolaos Mihalopoulos, Alexandros Papayannis, and Athanasios Nenes
Atmos. Chem. Phys., 16, 7389–7409, https://doi.org/10.5194/acp-16-7389-2016, https://doi.org/10.5194/acp-16-7389-2016, 2016
Short summary
Short summary
BBOA from long-range transport exhibits increased CCN concentrations for particles larger than 100 nm. At the same time the hygroscopicity parameter decreased for all particle sizes, as sub-100 nm particles appear to be richer in less hygroscopic organic material, while larger particles become less hygroscopic due to condensation of less hygroscopic gaseous compounds. Finally, atmospheric processing of freshly emitted BBOA to more oxidized organic aerosol can result in a 2-fold increase of κ.
Chih-Chieh Chen and Andrew Gettelman
Atmos. Chem. Phys., 16, 7317–7333, https://doi.org/10.5194/acp-16-7317-2016, https://doi.org/10.5194/acp-16-7317-2016, 2016
Short summary
Short summary
The impact of aviation emissions through 2050 is simulated by a comprehensive global climate model. Four different future emission scenarios of the same flight tracks are considered. The results reveal that the global radiative forcing of contrail cirrus is positive and can increase by a factor of 7 in 2050 from the 2006 level. The aviation aerosols can produce negative forcing, mainly over the oceans, and increase by a factor of 4 in 2050 from the 2006 level.
Swen Metzger, Benedikt Steil, Mohamed Abdelkader, Klaus Klingmüller, Li Xu, Joyce E. Penner, Christos Fountoukis, Athanasios Nenes, and Jos Lelieveld
Atmos. Chem. Phys., 16, 7213–7237, https://doi.org/10.5194/acp-16-7213-2016, https://doi.org/10.5194/acp-16-7213-2016, 2016
Short summary
Short summary
We introduce an unique single parameter framework to efficiently parameterize the aerosol water uptake for mixtures of semi-volatile and non-volatile compounds, being entirely based on the single solute specific coefficient introduced in Metzger et al. (2012).
Aikaterini Bougiatioti, Panayiota Nikolaou, Iasonas Stavroulas, Giorgos Kouvarakis, Rodney Weber, Athanasios Nenes, Maria Kanakidou, and Nikolaos Mihalopoulos
Atmos. Chem. Phys., 16, 4579–4591, https://doi.org/10.5194/acp-16-4579-2016, https://doi.org/10.5194/acp-16-4579-2016, 2016
Short summary
Short summary
Atmospheric aerosols and relevant parameters were measured in the eastern Mediterranean during summer and fall 2012. Submicron aerosol water can contribute up to 33 % of total mass, and 27.5 % of this can be associated with organics. Using these data, the pH of the submicron aerosols was calculated to be highly acidic, varying from 0.5 to 2.8 and independently of air masses origin. Such pH values could increase nutrient availability and thus sea water productivity of the Mediterranean Sea.
Christopher R. Hoyle, Clare S. Webster, Harald E. Rieder, Athanasios Nenes, Emanuel Hammer, Erik Herrmann, Martin Gysel, Nicolas Bukowiecki, Ernest Weingartner, Martin Steinbacher, and Urs Baltensperger
Atmos. Chem. Phys., 16, 4043–4061, https://doi.org/10.5194/acp-16-4043-2016, https://doi.org/10.5194/acp-16-4043-2016, 2016
Short summary
Short summary
A simple statistical model to predict the number of aerosols which activate to form cloud droplets in warm clouds has been established, based on regression analysis of data from the high-altitude site Jungfraujoch. It is found that cloud droplet formation at the Jungfraujoch is predominantly controlled by the number concentration of aerosol particles. A statistical model based on only the number of particles larger than 80nm can explain 79 % of the observed variance in droplet numbers.
Yong-ha Kim, Sotira Yiacoumi, Athanasios Nenes, and Costas Tsouris
Atmos. Chem. Phys., 16, 3449–3462, https://doi.org/10.5194/acp-16-3449-2016, https://doi.org/10.5194/acp-16-3449-2016, 2016
Short summary
Short summary
Three microphysical approaches are proposed to incorporate mutual effects of particle charging and coagulation in predictions of transient charge and size distributions of atmospheric particles, including radioactive aerosols. The three approaches have different levels of complexities and are applicable to various laboratory and field atmospheric studies. Also, these approaches can be easily incorporated into aerosol transport models at different scales to account for particle charging effects.
Shipeng Zhang, Minghuai Wang, Steven J. Ghan, Aijun Ding, Hailong Wang, Kai Zhang, David Neubauer, Ulrike Lohmann, Sylvaine Ferrachat, Toshihiko Takeamura, Andrew Gettelman, Hugh Morrison, Yunha Lee, Drew T. Shindell, Daniel G. Partridge, Philip Stier, Zak Kipling, and Congbin Fu
Atmos. Chem. Phys., 16, 2765–2783, https://doi.org/10.5194/acp-16-2765-2016, https://doi.org/10.5194/acp-16-2765-2016, 2016
Short summary
Short summary
The variation of aerosol indirect effects (AIE) in several climate models is investigated across different dynamical regimes. Regimes with strong large-scale ascent are shown to be as important as stratocumulus regimes in studying AIE. AIE over regions with high monthly large-scale surface precipitation rate contributes the most to the total aerosol indirect forcing. These results point to the need to reduce the uncertainty in AIE in different dynamical regimes.
Sylvia C. Sullivan, Ricardo Morales Betancourt, Donifan Barahona, and Athanasios Nenes
Atmos. Chem. Phys., 16, 2611–2629, https://doi.org/10.5194/acp-16-2611-2016, https://doi.org/10.5194/acp-16-2611-2016, 2016
Short summary
Short summary
We use the adjoint model of a cirrus parameterization to quantify sources of crystal variability for various ice-nucleating spectra and output from CAM5.
The sensitivities can be directly linked to nucleation regime and
efficiency of various INP.
The lab-based spectrum calculates much higher INP efficiencies than field-based ones, owing to aerosol surface properties.
The sensitivity to temperature tends to be low, due to the compensating effects of temperature on INP spectrum parameters.
Colin M. Zarzycki, Kevin A. Reed, Julio T. Bacmeister, Anthony P. Craig, Susan C. Bates, and Nan A. Rosenbloom
Geosci. Model Dev., 9, 779–788, https://doi.org/10.5194/gmd-9-779-2016, https://doi.org/10.5194/gmd-9-779-2016, 2016
Short summary
Short summary
This paper highlights the sensitivity of simulated tropical cyclone climatology to the choice of ocean coupling grid in high-resolution climate simulations. When computations of atmosphere–ocean interactions are carried out on the coarser grid in the system, key quantities such as surface wind drag and heat fluxes are incorrectly calculated. In the case of a coarser ocean grid, significantly stronger cyclone winds result, due to misaligned frictional vectors in the atmospheric dynamical core.
L. M. Zamora, R. A. Kahn, M. J. Cubison, G. S. Diskin, J. L. Jimenez, Y. Kondo, G. M. McFarquhar, A. Nenes, K. L. Thornhill, A. Wisthaler, A. Zelenyuk, and L. D. Ziemba
Atmos. Chem. Phys., 16, 715–738, https://doi.org/10.5194/acp-16-715-2016, https://doi.org/10.5194/acp-16-715-2016, 2016
Short summary
Short summary
Based on extensive aircraft campaigns, we quantify how biomass burning smoke affects subarctic and Arctic liquid cloud microphysical properties. Enhanced cloud albedo may decrease short-wave radiative flux by between 2 and 4 Wm2 or more in some subarctic conditions. Smoke halved average cloud droplet diameter. In one case study, it also appeared to limit droplet formation. Numerous Arctic background Aitken particles can also interact with combustion particles, perhaps affecting their properties.
D. Barahona
Atmos. Chem. Phys., 15, 13819–13831, https://doi.org/10.5194/acp-15-13819-2015, https://doi.org/10.5194/acp-15-13819-2015, 2015
Short summary
Short summary
This paper describes the process of the transfer of water molecules between liquid and the ice during the early stages of ice formation. Using concepts of nonreversible thermodynamics, it is shown that the activation energy can be defined in terms of the bulk self-diffusivity of water and the probability of interface transfer. The application of this model to classical nucleation theory shows good agreement of measured nucleation rates with experimental results for temperatures as low as 190K.
P. H. Lauritzen, J. T. Bacmeister, P. F. Callaghan, and M. A. Taylor
Geosci. Model Dev., 8, 3975–3986, https://doi.org/10.5194/gmd-8-3975-2015, https://doi.org/10.5194/gmd-8-3975-2015, 2015
Short summary
Short summary
This paper documents the NCAR global model topography generation software. The software generates elevation and related data for global atmospheric models based in GTOPO30 or GMTED2010/MODIS source data.
K. Thayer-Calder, A. Gettelman, C. Craig, S. Goldhaber, P. A. Bogenschutz, C.-C. Chen, H. Morrison, J. Höft, E. Raut, B. M. Griffin, J. K. Weber, V. E. Larson, M. C. Wyant, M. Wang, Z. Guo, and S. J. Ghan
Geosci. Model Dev., 8, 3801–3821, https://doi.org/10.5194/gmd-8-3801-2015, https://doi.org/10.5194/gmd-8-3801-2015, 2015
Short summary
Short summary
This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that is implemented in CAM v5.3. We show mean climate and tropical variability results from global simulations. The model has a degradation in precipitation skill but improvements in shortwave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. We also show estimation of computational expense and sensitivity to number of subcolumns.
A. Gettelman
Atmos. Chem. Phys., 15, 12397–12411, https://doi.org/10.5194/acp-15-12397-2015, https://doi.org/10.5194/acp-15-12397-2015, 2015
Short summary
Short summary
Aerosols affect cloud properties, and the radiative effects of clouds. Human emissions of aerosol particles and precursors may alter the radiative effects of clouds. This is generally a cooling effect that offsets other warming effects of human emissions of gases. Simulating these aerosol effects on clouds are highly dependent on the formulation of the microphysical (cloud droplet scale) processes. This work uses model simulations to show these effects are large, and depend on certain processes.
M. Paramonov, V.-M. Kerminen, M. Gysel, P. P. Aalto, M. O. Andreae, E. Asmi, U. Baltensperger, A. Bougiatioti, D. Brus, G. P. Frank, N. Good, S. S. Gunthe, L. Hao, M. Irwin, A. Jaatinen, Z. Jurányi, S. M. King, A. Kortelainen, A. Kristensson, H. Lihavainen, M. Kulmala, U. Lohmann, S. T. Martin, G. McFiggans, N. Mihalopoulos, A. Nenes, C. D. O'Dowd, J. Ovadnevaite, T. Petäjä, U. Pöschl, G. C. Roberts, D. Rose, B. Svenningsson, E. Swietlicki, E. Weingartner, J. Whitehead, A. Wiedensohler, C. Wittbom, and B. Sierau
Atmos. Chem. Phys., 15, 12211–12229, https://doi.org/10.5194/acp-15-12211-2015, https://doi.org/10.5194/acp-15-12211-2015, 2015
Short summary
Short summary
The research paper presents the first comprehensive overview of field measurements with the CCN Counter performed at a large number of locations around the world within the EUCAARI framework. The paper sheds light on the CCN number concentrations and activated fractions around the world and their dependence on the water vapour supersaturation ratio, the dependence of aerosol hygroscopicity on particle size, and seasonal and diurnal variation of CCN activation and hygroscopic properties.
N. Kalivitis, V.-M. Kerminen, G. Kouvarakis, I. Stavroulas, A. Bougiatioti, A. Nenes, H. E. Manninen, T. Petäjä, M. Kulmala, and N. Mihalopoulos
Atmos. Chem. Phys., 15, 9203–9215, https://doi.org/10.5194/acp-15-9203-2015, https://doi.org/10.5194/acp-15-9203-2015, 2015
Short summary
Short summary
Cloud condensation nuclei (CCN) production associated with atmospheric new particle formation (NPF) is presented, and this is the first direct evidence of CCN production resulting from NPF in the eastern Mediterranean atmosphere. We show that condensation of both gaseous sulfuric acid and organic compounds from multiple sources leads to the rapid growth of nucleated particles. Sub-100nm particles were found to be substantially less hygroscopic than larger particles during the active NPF period.
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, https://doi.org/10.5194/acp-15-8871-2015, https://doi.org/10.5194/acp-15-8871-2015, 2015
Short summary
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.
K. M. Cerully, A. Bougiatioti, J. R. Hite Jr., H. Guo, L. Xu, N. L. Ng, R. Weber, and A. Nenes
Atmos. Chem. Phys., 15, 8679–8694, https://doi.org/10.5194/acp-15-8679-2015, https://doi.org/10.5194/acp-15-8679-2015, 2015
Short summary
Short summary
The hygroscopicity of SE US aerosol is mostly water-soluble, with a hygroscopicity that is insensitive to partial volatilization in a thermodenuder.
The most and least oxidized components of the aerosol are the most hygroscopic of organic constituents.
No clear relationship was found between organic aerosol hygroscopicity and oxygen-to-carbon ratio.
The aerosol factors covary in a way that induces the observed diurnal invariance in total organic hygroscopicity.
L. Hildebrandt Ruiz, A. L. Paciga, K. M. Cerully, A. Nenes, N. M. Donahue, and S. N. Pandis
Atmos. Chem. Phys., 15, 8301–8313, https://doi.org/10.5194/acp-15-8301-2015, https://doi.org/10.5194/acp-15-8301-2015, 2015
Short summary
Short summary
Secondary organic aerosol (SOA) is transformed after its initial formation. We explored the effects of this chemical aging on the composition, mass yield, volatility, and hygroscopicity of SOA formed from the photo-oxidation of small aromatic volatile organic compounds. Higher exposure to the hydroxyl radical resulted in different SOA composition, average carbon oxidation state, and mass yield. The vapor pressure of SOA formed under different conditions varied by as much as a factor of 30.
Y. Shinozuka, A. D. Clarke, A. Nenes, A. Jefferson, R. Wood, C. S. McNaughton, J. Ström, P. Tunved, J. Redemann, K. L. Thornhill, R. H. Moore, T. L. Lathem, J. J. Lin, and Y. J. Yoon
Atmos. Chem. Phys., 15, 7585–7604, https://doi.org/10.5194/acp-15-7585-2015, https://doi.org/10.5194/acp-15-7585-2015, 2015
S. Myriokefalitakis, N. Daskalakis, N. Mihalopoulos, A. R. Baker, A. Nenes, and M. Kanakidou
Biogeosciences, 12, 3973–3992, https://doi.org/10.5194/bg-12-3973-2015, https://doi.org/10.5194/bg-12-3973-2015, 2015
Short summary
Short summary
The global atmospheric cycle of Fe is simulated accounting for natural and combustion sources, proton- and organic ligand-promoted Fe dissolution from dust aerosol and changes in anthropogenic emissions, and thus in atmospheric acidity. Simulations show that Fe dissolution may have increased in the last 150 years and is expected to decrease due to air pollution regulations. Reductions in dissolved-Fe deposition can further limit the primary productivity over high-nutrient-low-chlorophyll water.
A. Molod, L. Takacs, M. Suarez, and J. Bacmeister
Geosci. Model Dev., 8, 1339–1356, https://doi.org/10.5194/gmd-8-1339-2015, https://doi.org/10.5194/gmd-8-1339-2015, 2015
H. Guo, L. Xu, A. Bougiatioti, K. M. Cerully, S. L. Capps, J. R. Hite Jr., A. G. Carlton, S.-H. Lee, M. H. Bergin, N. L. Ng, A. Nenes, and R. J. Weber
Atmos. Chem. Phys., 15, 5211–5228, https://doi.org/10.5194/acp-15-5211-2015, https://doi.org/10.5194/acp-15-5211-2015, 2015
Short summary
Short summary
Particle pH can affect many aerosol processes, including gas-particle partitioning, SOA formation, and mobilization of toxic redox metals. pH is challenging to directly measure and often improperly characterized by proxies like ion balances or molar ratios of measured aerosol ionic species. We present a detailed analysis predicting pH with a thermodynamic model, verify the prediction, and test pH sensitivity to model inputs based on data from the SOAS field campaign.
C. J. Hennigan, J. Izumi, A. P. Sullivan, R. J. Weber, and A. Nenes
Atmos. Chem. Phys., 15, 2775–2790, https://doi.org/10.5194/acp-15-2775-2015, https://doi.org/10.5194/acp-15-2775-2015, 2015
Short summary
Short summary
We show that the ion balance and molar ratio methods are unsuitable for use as aerosol pH proxies. Our recommendation is that 1) thermodynamic equilibrium models constrained by both gas and aerosol inputs run in the forward (open) mode, and 2) the phase partitioning of ammonia provides the best predictions of aerosol pH. Given the significance of acidity for numerous chemical processes in the atmosphere, the implications of this study are important and far reaching.
Y. You, V. P. Kanawade, J. A. de Gouw, A. B. Guenther, S. Madronich, M. R. Sierra-Hernández, M. Lawler, J. N. Smith, S. Takahama, G. Ruggeri, A. Koss, K. Olson, K. Baumann, R. J. Weber, A. Nenes, H. Guo, E. S. Edgerton, L. Porcelli, W. H. Brune, A. H. Goldstein, and S.-H. Lee
Atmos. Chem. Phys., 14, 12181–12194, https://doi.org/10.5194/acp-14-12181-2014, https://doi.org/10.5194/acp-14-12181-2014, 2014
Short summary
Short summary
Amiens play important roles in atmospheric secondary aerosol formation and human health, but the fast response measurements of amines are lacking. Here we show measurements in a southeastern US forest and a moderately polluted midwestern site. Our results show that gas to particle conversion is an important process that controls ambient amine concentrations and that biomass burning is an important source of amines.
R. Morales Betancourt and A. Nenes
Geosci. Model Dev., 7, 2345–2357, https://doi.org/10.5194/gmd-7-2345-2014, https://doi.org/10.5194/gmd-7-2345-2014, 2014
T. Eidhammer, H. Morrison, A. Bansemer, A. Gettelman, and A. J. Heymsfield
Atmos. Chem. Phys., 14, 10103–10118, https://doi.org/10.5194/acp-14-10103-2014, https://doi.org/10.5194/acp-14-10103-2014, 2014
M. S. Johnston, S. Eliasson, P. Eriksson, R. M. Forbes, A. Gettelman, P. Räisänen, and M. D. Zelinka
Atmos. Chem. Phys., 14, 8701–8721, https://doi.org/10.5194/acp-14-8701-2014, https://doi.org/10.5194/acp-14-8701-2014, 2014
D. Barahona
Atmos. Chem. Phys., 14, 7665–7680, https://doi.org/10.5194/acp-14-7665-2014, https://doi.org/10.5194/acp-14-7665-2014, 2014
B. Gantt, J. He, X. Zhang, Y. Zhang, and A. Nenes
Atmos. Chem. Phys., 14, 7485–7497, https://doi.org/10.5194/acp-14-7485-2014, https://doi.org/10.5194/acp-14-7485-2014, 2014
G. Drozd, J. Woo, S. A. K. Häkkinen, A. Nenes, and V. F. McNeill
Atmos. Chem. Phys., 14, 5205–5215, https://doi.org/10.5194/acp-14-5205-2014, https://doi.org/10.5194/acp-14-5205-2014, 2014
S. Romakkaniemi, A. Jaatinen, A. Laaksonen, A. Nenes, and T. Raatikainen
Atmos. Meas. Tech., 7, 1377–1384, https://doi.org/10.5194/amt-7-1377-2014, https://doi.org/10.5194/amt-7-1377-2014, 2014
A. Bougiatioti, I. Stavroulas, E. Kostenidou, P. Zarmpas, C. Theodosi, G. Kouvarakis, F. Canonaco, A. S. H. Prévôt, A. Nenes, S. N. Pandis, and N. Mihalopoulos
Atmos. Chem. Phys., 14, 4793–4807, https://doi.org/10.5194/acp-14-4793-2014, https://doi.org/10.5194/acp-14-4793-2014, 2014
R. Morales Betancourt and A. Nenes
Atmos. Chem. Phys., 14, 4809–4826, https://doi.org/10.5194/acp-14-4809-2014, https://doi.org/10.5194/acp-14-4809-2014, 2014
C.-C. Chen and A. Gettelman
Atmos. Chem. Phys., 13, 12525–12536, https://doi.org/10.5194/acp-13-12525-2013, https://doi.org/10.5194/acp-13-12525-2013, 2013
A. Gettelman, H. Morrison, C. R. Terai, and R. Wood
Atmos. Chem. Phys., 13, 9855–9867, https://doi.org/10.5194/acp-13-9855-2013, https://doi.org/10.5194/acp-13-9855-2013, 2013
M. Trail, A. P. Tsimpidi, P. Liu, K. Tsigaridis, Y. Hu, A. Nenes, and A. G. Russell
Geosci. Model Dev., 6, 1429–1445, https://doi.org/10.5194/gmd-6-1429-2013, https://doi.org/10.5194/gmd-6-1429-2013, 2013
S. Lance, T. Raatikainen, T. B. Onasch, D. R. Worsnop, X.-Y. Yu, M. L. Alexander, M. R. Stolzenburg, P. H. McMurry, J. N. Smith, and A. Nenes
Atmos. Chem. Phys., 13, 5049–5062, https://doi.org/10.5194/acp-13-5049-2013, https://doi.org/10.5194/acp-13-5049-2013, 2013
R. H. Moore, V. A. Karydis, S. L. Capps, T. L. Lathem, and A. Nenes
Atmos. Chem. Phys., 13, 4235–4251, https://doi.org/10.5194/acp-13-4235-2013, https://doi.org/10.5194/acp-13-4235-2013, 2013
J.-I. Yano, M. Bister, Ž. Fuchs, L. Gerard, V. T. J. Phillips, S. Barkidija, and J.-M. Piriou
Atmos. Chem. Phys., 13, 4111–4131, https://doi.org/10.5194/acp-13-4111-2013, https://doi.org/10.5194/acp-13-4111-2013, 2013
T. L. Lathem, A. J. Beyersdorf, K. L. Thornhill, E. L. Winstead, M. J. Cubison, A. Hecobian, J. L. Jimenez, R. J. Weber, B. E. Anderson, and A. Nenes
Atmos. Chem. Phys., 13, 2735–2756, https://doi.org/10.5194/acp-13-2735-2013, https://doi.org/10.5194/acp-13-2735-2013, 2013
M. Frosch, M. Bilde, A. Nenes, A. P. Praplan, Z. Jurányi, J. Dommen, M. Gysel, E. Weingartner, and U. Baltensperger
Atmos. Chem. Phys., 13, 2283–2297, https://doi.org/10.5194/acp-13-2283-2013, https://doi.org/10.5194/acp-13-2283-2013, 2013
Y. C. Sud, D. Lee, L. Oreopoulos, D. Barahona, A. Nenes, and M. J. Suarez
Geosci. Model Dev., 6, 57–79, https://doi.org/10.5194/gmd-6-57-2013, https://doi.org/10.5194/gmd-6-57-2013, 2013
Related subject area
Atmospheric sciences
Implementation of HONO into the chemistry–climate model CHASER (V4.0): roles in tropospheric chemistry
Isoprene and monoterpene simulations using the chemistry–climate model EMAC (v2.55) with interactive vegetation from LPJ-GUESS (v4.0)
A modern-day Mars climate in the Met Office Unified Model: dry simulations
The AirGAM 2022r1 air quality trend and prediction model
Evaluation of a cloudy cold-air pool in the Columbia River basin in different versions of the High-Resolution Rapid Refresh (HRRR) model
Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS regional air quality ensemble
Cross-evaluating WRF-Chem v4.1.2, TROPOMI, APEX, and in situ NO2 measurements over Antwerp, Belgium
Adapting a deep convolutional RNN model with imbalanced regression loss for improved spatio-temporal forecasting of extreme wind speed events in the short to medium range
ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application
Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model: RegCM
The E3SM Diagnostics Package (E3SM Diags v2.7): a Python-based diagnostics package for Earth system model evaluation
A method for transporting cloud-resolving model variance in a multiscale modeling framework
The Mission Support System (MSS v7.0.4) and its use in planning for the SouthTRAC aircraft campaign
GENerator of reduced Organic Aerosol mechanism (GENOA v1.0): an automatic generation tool of semi-explicit mechanisms
Representing chemical history in ozone time-series predictions – a model experiment study building on the MLAir (v1.5) deep learning framework
Evaluation of high-resolution predictions of fine particulate matter and its composition in an urban area using PMCAMx-v2.0
A local data assimilation method (Local DA v1.0) and its application in a simulated typhoon case
Improved advection, resolution, performance, and community access in the new generation (version 13) of the high-performance GEOS-Chem global atmospheric chemistry model (GCHP)
Lightning assimilation in the WRF model (Version 4.1.1): technique updates and assessment of the applications from regional to hemispheric scales
Optimization of snow-related parameters in the Noah land surface model (v3.4.1) using a micro-genetic algorithm (v1.7a)
Development of an LSTM broadcasting deep-learning framework for regional air pollution forecast improvement
A local particle filter and its Gaussian mixture extension implemented with minor modifications to the LETKF
A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions
Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1)
Evaluation of the NAQFC driven by the NOAA Global Forecast System (version 16): comparison with the WRF-CMAQ during the summer 2019 FIREX-AQ campaign
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 1.0.0): EnVar implementation and evaluation
Development of a regional feature selection-based machine learning system (RFSML v1.0) for air pollution forecasting over China
A lumped species approach for the simulation of secondary organic aerosol production from intermediate-volatility organic compounds (IVOCs): application to road transport in PMCAMx-iv (v1.0)
AerSett v1.0: A simple and straightforward model for the settling speed of big spherical atmospheric aerosol
TrackMatcher – a tool for finding intercepts in tracks of geographical positions
Recovery of sparse urban greenhouse gas emissions
Tropospheric transport and unresolved convection: numerical experiments with CLaMS 2.0/MESSy
MUNICH v2.0: a street-network model coupled with SSH-aerosol (v1.2) for multi-pollutant modelling
A preliminary evaluation of FY-4A visible radiance data assimilation by the WRF (ARW v4.1.1)/DART (Manhattan release v9.8.0)-RTTOV (v12.3) system for a tropical storm case
Repeatable high-resolution statistical downscaling through deep learning
The second Met Office Unified Model/JULES Regional Atmosphere and Land configuration, RAL2
Atmospherically Relevant Chemistry and Aerosol box model – ARCA box (version 1.2)
MultilayerPy (v1.0): a Python-based framework for building, running and optimising kinetic multi-layer models of aerosols and films
Introduction of the DISAMAR radiative transfer model: determining instrument specifications and analysing methods for atmospheric retrieval (version 4.1.5)
Assessment of the data assimilation framework for the Rapid Refresh Forecast System v0.1 and impacts on forecasts of a convective storm case study
Downscaling atmospheric chemistry simulations with physically consistent deep learning
Bayesian transdimensional inverse reconstruction of the 137Cs Fukushima-Daiichi release
Incorporation of aerosols into the COSPv2 satellite lidar simulator for climate model evaluation
A machine learning methodology for the generation of a parameterization of the hydroxyl radical
Large-eddy simulations with ClimateMachine v0.2.0: a new open-source code for atmospheric simulations on GPUs and CPUs
Hybrid ensemble-variational data assimilation in ABC-DA within a tropical framework
OpenIFS/AC: atmospheric chemistry and aerosol in OpenIFS 43r3
Simulations of aerosol pH in China using WRF-Chem (v4.0): sensitivities of aerosol pH and its temporal variations during haze episodes
Deep learning models for generation of precipitation maps based on Numerical Weather Prediction
A daily highest air temperature estimation method and spatial–temporal changes analysis of high temperature in China from 1979 to 2018
Phuc Thi Minh Ha, Yugo Kanaya, Fumikazu Taketani, Maria Dolores Andrés Hernández, Benjamin Schreiner, Klaus Pfeilsticker, and Kengo Sudo
Geosci. Model Dev., 16, 927–960, https://doi.org/10.5194/gmd-16-927-2023, https://doi.org/10.5194/gmd-16-927-2023, 2023
Short summary
Short summary
HONO affects tropospheric oxidizing capacity; thus, it is implemented into the chemistry–climate model CHASER. The model substantially underpredicts daytime HONO, while nitrate photolysis on surfaces can supplement the daytime HONO budget. Current HONO chemistry predicts reductions of 20.4 % for global tropospheric NOx, 40–67 % for OH, and 30–45 % for O3 in the summer North Pacific. In contrast, OH and O3 winter levels in China are greatly enhanced.
Ryan Vella, Matthew Forrest, Jos Lelieveld, and Holger Tost
Geosci. Model Dev., 16, 885–906, https://doi.org/10.5194/gmd-16-885-2023, https://doi.org/10.5194/gmd-16-885-2023, 2023
Short summary
Short summary
Biogenic volatile organic compounds (BVOCs) are released by vegetation and have a major impact on atmospheric chemistry and aerosol formation. Non-interacting vegetation constrains the majority of numerical models used to estimate global BVOC emissions, and thus, the effects of changing vegetation on emissions are not addressed. In this work, we replace the offline vegetation with dynamic vegetation states by linking a chemistry–climate model with a global dynamic vegetation model.
Danny McCulloch, Denis E. Sergeev, Nathan Mayne, Matthew Bate, James Manners, Ian Boutle, Benjamin Drummond, and Kristzian Kohary
Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023, https://doi.org/10.5194/gmd-16-621-2023, 2023
Short summary
Short summary
We present results from the Met Office Unified Model (UM) to study the dry Martian climate. We describe our model set-up conditions and run two scenarios, with radiatively active/inactive dust. We compare both scenarios to results from an existing Mars climate model, the planetary climate model. We find good agreement in winds and air temperatures, but dust amounts differ between models. This study highlights the importance of using the UM for future Mars research.
Sam-Erik Walker, Sverre Solberg, Philipp Schneider, and Cristina Guerreiro
Geosci. Model Dev., 16, 573–595, https://doi.org/10.5194/gmd-16-573-2023, https://doi.org/10.5194/gmd-16-573-2023, 2023
Short summary
Short summary
We have developed a statistical model for estimating trends in the daily air quality observations of NO2, O3, PM10 and PM2.5, adjusting for trends and short-term variations in meteorology. The model is general and may also be used for prediction purposes, including forecasting. It has been applied in a recent comprehensive study in Europe. Significant declines are shown for the pollutants from 2005 to 2019, mainly due to reductions in emissions not attributable to changes in meteorology.
Bianca Adler, James M. Wilczak, Jaymes Kenyon, Laura Bianco, Irina V. Djalalova, Joseph B. Olson, and David D. Turner
Geosci. Model Dev., 16, 597–619, https://doi.org/10.5194/gmd-16-597-2023, https://doi.org/10.5194/gmd-16-597-2023, 2023
Short summary
Short summary
Rapid changes in wind speed make the integration of wind energy produced during persistent orographic cold-air pools difficult to integrate into the electrical grid. By evaluating three versions of NOAA’s High-Resolution Rapid Refresh model, we demonstrate how model developments targeted during the second Wind Forecast Improvement Project improve the forecast of a persistent cold-air pool event.
John Douros, Henk Eskes, Jos van Geffen, K. Folkert Boersma, Steven Compernolle, Gaia Pinardi, Anne-Marlene Blechschmidt, Vincent-Henri Peuch, Augustin Colette, and Pepijn Veefkind
Geosci. Model Dev., 16, 509–534, https://doi.org/10.5194/gmd-16-509-2023, https://doi.org/10.5194/gmd-16-509-2023, 2023
Short summary
Short summary
We focus on the challenges associated with comparing atmospheric composition models with satellite products such as tropospheric NO2 columns. The aim is to highlight the methodological difficulties and propose sound ways of doing such comparisons. Building on the comparisons, a new satellite product is proposed and made available, which takes advantage of higher-resolution, regional atmospheric modelling to improve estimates of troposheric NO2 columns over Europe.
Catalina Poraicu, Jean-François Müller, Trissevgeni Stavrakou, Dominique Fonteyn, Frederik Tack, Felix Deutsch, Quentin Laffineur, Roeland Van Malderen, and Nele Veldeman
Geosci. Model Dev., 16, 479–508, https://doi.org/10.5194/gmd-16-479-2023, https://doi.org/10.5194/gmd-16-479-2023, 2023
Short summary
Short summary
High-resolution WRF-Chem simulations are conducted over Antwerp, Belgium, in June 2019 and evaluated using meteorological data and in situ, airborne, and spaceborne NO2 measurements. An intercomparison of model, aircraft, and TROPOMI NO2 columns is conducted to characterize biases in versions 1.3.1 and 2.3.1 of the satellite product. A mass balance method is implemented to provide improved emissions for simulating NO2 distribution over the study area.
Daan R. Scheepens, Irene Schicker, Kateřina Hlaváčková-Schindler, and Claudia Plant
Geosci. Model Dev., 16, 251–270, https://doi.org/10.5194/gmd-16-251-2023, https://doi.org/10.5194/gmd-16-251-2023, 2023
Short summary
Short summary
The production of wind energy is increasing rapidly and relies heavily on atmospheric conditions. To ensure power grid stability, accurate predictions of wind speed are needed, especially in the short range and for extreme wind speed ranges. In this work, we demonstrate the forecasting skills of a data-driven deep learning model with model adaptations to suit higher wind speed ranges. The resulting model can be applied to other data and parameters, too, to improve nowcasting predictions.
Peter J. M. Bosman and Maarten C. Krol
Geosci. Model Dev., 16, 47–74, https://doi.org/10.5194/gmd-16-47-2023, https://doi.org/10.5194/gmd-16-47-2023, 2023
Short summary
Short summary
We describe an inverse modelling framework constructed around a simple model for the atmospheric boundary layer. This framework can be fed with various observation types to study the boundary layer and land–atmosphere exchange. With this framework, it is possible to estimate model parameters and the associated uncertainties. Some of these parameters are difficult to obtain directly by observations. An example application for a grassland in the Netherlands is included.
Sudipta Ghosh, Sagnik Dey, Sushant Das, Nicole Riemer, Graziano Giuliani, Dilip Ganguly, Chandra Venkataraman, Filippo Giorgi, Sachchida Nand Tripathi, Srikanthan Ramachandran, Thazhathakal Ayyappen Rajesh, Harish Gadhavi, and Atul Kumar Srivastava
Geosci. Model Dev., 16, 1–15, https://doi.org/10.5194/gmd-16-1-2023, https://doi.org/10.5194/gmd-16-1-2023, 2023
Short summary
Short summary
Accurate representation of aerosols in climate models is critical for minimizing the uncertainty in climate projections. Here, we implement region-specific emission fluxes and a more accurate scheme for carbonaceous aerosol ageing processes in a regional climate model (RegCM4) and show that it improves model performance significantly against in situ, reanalysis, and satellite data over the Indian subcontinent. We recommend improving the model performance before using them for climate studies.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
Short summary
Short summary
Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Walter Hannah and Kyle Pressel
Geosci. Model Dev., 15, 8999–9013, https://doi.org/10.5194/gmd-15-8999-2022, https://doi.org/10.5194/gmd-15-8999-2022, 2022
Short summary
Short summary
A multiscale modeling framework couples two models of the atmosphere that each cover different scale ranges. Traditionally, fluctuations in the small-scale model are not transported by the flow on the large-scale model grid, but this is hypothesized to be responsible for a persistent, unphysical checkerboard pattern. A method is presented to facilitate the transport of these small-scale fluctuations, analogous to how small-scale clouds and turbulence are transported in the real atmosphere.
Reimar Bauer, Jens-Uwe Grooß, Jörn Ungermann, May Bär, Markus Geldenhuys, and Lars Hoffmann
Geosci. Model Dev., 15, 8983–8997, https://doi.org/10.5194/gmd-15-8983-2022, https://doi.org/10.5194/gmd-15-8983-2022, 2022
Short summary
Short summary
The Mission Support System (MSS) is an open source software package that has been used for planning flight tracks of scientific aircraft in multiple measurement campaigns during the last decade. Here, we describe the MSS software and its use during the SouthTRAC measurement campaign in 2019. As an example for how the MSS software is used in conjunction with many datasets, we describe the planning of a single flight probing orographic gravity waves propagating up into the lower mesosphere.
Zhizhao Wang, Florian Couvidat, and Karine Sartelet
Geosci. Model Dev., 15, 8957–8982, https://doi.org/10.5194/gmd-15-8957-2022, https://doi.org/10.5194/gmd-15-8957-2022, 2022
Short summary
Short summary
Air quality models need to reliably predict secondary organic aerosols (SOAs) at a reasonable computational cost. Thus, we developed GENOA v1.0, a mechanism reduction algorithm that preserves the accuracy of detailed gas-phase chemical mechanisms for SOA formation, thereby improving the practical use of actual chemistry in SOA models. With GENOA, a near-explicit chemical scheme was reduced to 2 % of its original size and computational time, with an average error of less than 3 %.
Felix Kleinert, Lukas H. Leufen, Aurelia Lupascu, Tim Butler, and Martin G. Schultz
Geosci. Model Dev., 15, 8913–8930, https://doi.org/10.5194/gmd-15-8913-2022, https://doi.org/10.5194/gmd-15-8913-2022, 2022
Short summary
Short summary
We examine the effects of spatially aggregated upstream information as input for a deep learning model forecasting near-surface ozone levels. Using aggregated data from one upstream sector (45°) improves the forecast by ~ 10 % for 4 prediction days. Three upstream sectors improve the forecasts by ~ 14 % on the first 2 d only. Our results serve as an orientation for other researchers or environmental agencies focusing on pointwise time-series predictions, for example, due to regulatory purposes.
Brian T. Dinkelacker, Pablo Garcia Rivera, Ioannis Kioutsioukis, Peter J. Adams, and Spyros N. Pandis
Geosci. Model Dev., 15, 8899–8912, https://doi.org/10.5194/gmd-15-8899-2022, https://doi.org/10.5194/gmd-15-8899-2022, 2022
Short summary
Short summary
The performance of a chemical transport model in reproducing PM2.5 concentrations and composition was evaluated at the finest scale using measurements from regulatory sites as well as a network of low-cost monitors. Total PM2.5 mass is reproduced well by the model during the winter when compared to regulatory measurements, but in the summer PM2.5 is underpredicted, mainly due to difficulties in reproducing regional secondary organic aerosol levels.
Shizhang Wang and Xiaoshi Qiao
Geosci. Model Dev., 15, 8869–8897, https://doi.org/10.5194/gmd-15-8869-2022, https://doi.org/10.5194/gmd-15-8869-2022, 2022
Short summary
Short summary
A local data assimilation scheme (Local DA v1.0) was proposed to leverage the advantage of hybrid covariance, multiscale localization, and parallel computation. The Local DA can perform covariance localization in model space, observation space, or both spaces. The Local DA that used the hybrid covariance and double-space localization produced the lowest analysis and forecast errors among all observing system simulation experiments.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, https://doi.org/10.5194/gmd-15-8731-2022, 2022
Short summary
Short summary
Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as standalone models. The widely used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the offline high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores, including on the cloud, with improved access, performance, and accuracy.
Daiwen Kang, Nicholas K. Heath, Robert C. Gilliam, Tanya L. Spero, and Jonathan E. Pleim
Geosci. Model Dev., 15, 8561–8579, https://doi.org/10.5194/gmd-15-8561-2022, https://doi.org/10.5194/gmd-15-8561-2022, 2022
Short summary
Short summary
A lightning assimilation (LTA) technique implemented in the WRF model's Kain–Fritsch (KF) convective scheme is updated and applied to simulations from regional to hemispheric scales using observed lightning flashes from ground-based lightning detection networks. Different user-toggled options associated with the KF scheme on simulations with and without LTA are assessed. The model's performance is improved significantly by LTA, but it is sensitive to various factors.
Sujeong Lim, Hyeon-Ju Gim, Ebony Lee, Seungyeon Lee, Won Young Lee, Yong Hee Lee, Claudio Cassardo, and Seon Ki Park
Geosci. Model Dev., 15, 8541–8559, https://doi.org/10.5194/gmd-15-8541-2022, https://doi.org/10.5194/gmd-15-8541-2022, 2022
Short summary
Short summary
The land surface model (LSM) contains various uncertain parameters, which are obtained by the empirical relations reflecting the specific local region and can be a source of uncertainty. To seek the optimal parameter values in the snow-related processes of the Noah LSM over South Korea, we have implemented an optimization algorithm, a micro-genetic algorithm using the observations. As a result, the optimized snow parameters improve snowfall prediction.
Haochen Sun, Jimmy C. H. Fung, Yiang Chen, Zhenning Li, Dehao Yuan, Wanying Chen, and Xingcheng Lu
Geosci. Model Dev., 15, 8439–8452, https://doi.org/10.5194/gmd-15-8439-2022, https://doi.org/10.5194/gmd-15-8439-2022, 2022
Short summary
Short summary
This study developed a novel deep-learning layer, the broadcasting layer, to build an end-to-end LSTM-based deep-learning model for regional air pollution forecast. By combining the ground observation, WRF-CMAQ simulation, and the broadcasting LSTM deep-learning model, forecast accuracy has been significantly improved when compared to other methods. The broadcasting layer and its variants can also be applied in other research areas to supersede the traditional numerical interpolation methods.
Shunji Kotsuki, Takemasa Miyoshi, Keiichi Kondo, and Roland Potthast
Geosci. Model Dev., 15, 8325–8348, https://doi.org/10.5194/gmd-15-8325-2022, https://doi.org/10.5194/gmd-15-8325-2022, 2022
Short summary
Short summary
Data assimilation plays an important part in numerical weather prediction (NWP) in terms of combining forecasted states and observations. While data assimilation methods in NWP usually assume the Gaussian error distribution, some variables in the atmosphere, such as precipitation, are known to have non-Gaussian error statistics. This study extended a widely used ensemble data assimilation algorithm to enable the assimilation of more non-Gaussian observations.
Martin Vojta, Andreas Plach, Rona L. Thompson, and Andreas Stohl
Geosci. Model Dev., 15, 8295–8323, https://doi.org/10.5194/gmd-15-8295-2022, https://doi.org/10.5194/gmd-15-8295-2022, 2022
Short summary
Short summary
In light of recent global warming, we aim to improve methods for modeling greenhouse gas emissions in order to support the successful implementation of the Paris Agreement. In this study, we investigate certain aspects of a Bayesian inversion method that uses computer simulations and atmospheric observations to improve estimates of greenhouse gas emissions. We explore method limitations, discuss problems, and suggest improvements.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
Short summary
Short summary
This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Youhua Tang, Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang
Geosci. Model Dev., 15, 7977–7999, https://doi.org/10.5194/gmd-15-7977-2022, https://doi.org/10.5194/gmd-15-7977-2022, 2022
Short summary
Short summary
This paper compares two meteorological datasets for driving a regional air quality model: a regional meteorological model using WRF (WRF-CMAQ) and direct interpolation from an operational global model (GFS-CMAQ). In the comparison with surface measurements and aircraft data in summer 2019, these two methods show mixed performance depending on the corresponding meteorological settings. Direct interpolation is found to be a viable method to drive air quality models.
Zhiquan Liu, Chris Snyder, Jonathan J. Guerrette, Byoung-Joo Jung, Junmei Ban, Steven Vahl, Yali Wu, Yannick Trémolet, Thomas Auligné, Benjamin Ménétrier, Anna Shlyaeva, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 15, 7859–7878, https://doi.org/10.5194/gmd-15-7859-2022, https://doi.org/10.5194/gmd-15-7859-2022, 2022
Short summary
Short summary
JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the MPAS model, was publicly released for community use. This article describes JEDI-MPAS's implementation of the ensemble–variational DA technique and demonstrates its robustness and credible performance by incrementally adding three types of microwave radiances (clear-sky AMSU-A, all-sky AMSU-A, clear-sky MHS) to a non-radiance DA experiment. We intend to periodically release new and improved versions of JEDI-MPAS in upcoming years.
Li Fang, Jianbing Jin, Arjo Segers, Hai Xiang Lin, Mijie Pang, Cong Xiao, Tuo Deng, and Hong Liao
Geosci. Model Dev., 15, 7791–7807, https://doi.org/10.5194/gmd-15-7791-2022, https://doi.org/10.5194/gmd-15-7791-2022, 2022
Short summary
Short summary
This study proposes a regional feature selection-based machine learning system to predict short-term air quality in China. The system has a tool that can figure out the importance of input data for better prediction. It provides large-scale air quality prediction that exhibits improved interpretability, fewer training costs, and higher accuracy compared with a standard machine learning system. It can act as an early warning for citizens and reduce exposure to PM2.5 and other air pollutants.
Stella E. I. Manavi and Spyros N. Pandis
Geosci. Model Dev., 15, 7731–7749, https://doi.org/10.5194/gmd-15-7731-2022, https://doi.org/10.5194/gmd-15-7731-2022, 2022
Short summary
Short summary
The paper describes the first step towards the development of a simulation framework for the chemistry and secondary organic aerosol production of intermediate-volatility organic compounds (IVOCs). These compounds can be a significant source of organic particulate matter. Our approach treats IVOCs as lumped compounds that retain their chemical characteristics. Estimated IVOC emissions from road transport were a factor of 8 higher than emissions used in previous applications.
Sylvain Mailler, Laurent Menut, Arineh Cholakian, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-247, https://doi.org/10.5194/gmd-2022-247, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
Large or even "giant" particles of mineral dust exist in the atmosphere but, so far, solving an non-linear equation was needed to calculate the speed at which they fall to the atmosphere. The model we present, SettAer v1.0, provides a new and simple way of calculating their free-fall velocity in the atmosphere, which will be useful to anyone trying to understand and represent adequately the transport of giant dust particles by the wind.
Peter Bräuer and Matthias Tesche
Geosci. Model Dev., 15, 7557–7572, https://doi.org/10.5194/gmd-15-7557-2022, https://doi.org/10.5194/gmd-15-7557-2022, 2022
Short summary
Short summary
This paper presents a tool for (i) finding temporally and spatially resolved intersections between two- or three-dimensional geographical tracks (trajectories) and (ii) extracting of data in the vicinity of intersections to achieve the optimal combination of various data sets.
Benjamin Zanger, Jia Chen, Man Sun, and Florian Dietrich
Geosci. Model Dev., 15, 7533–7556, https://doi.org/10.5194/gmd-15-7533-2022, https://doi.org/10.5194/gmd-15-7533-2022, 2022
Short summary
Short summary
Gaussian priors (GPs) used in least squares inversion do not reflect the true distributions of greenhouse gas emissions well. A method that does not rely on GPs is sparse reconstruction (SR). We show that necessary conditions for SR are satisfied for cities and that the application of a wavelet transform can further enhance sparsity. We apply the theory of compressed sensing to SR. Our results show that SR needs fewer measurements and is superior for assessing unknown emitters compared to GPs.
Paul Konopka, Mengchu Tao, Marc von Hobe, Lars Hoffmann, Corinna Kloss, Fabrizio Ravegnani, C. Michael Volk, Valentin Lauther, Andreas Zahn, Peter Hoor, and Felix Ploeger
Geosci. Model Dev., 15, 7471–7487, https://doi.org/10.5194/gmd-15-7471-2022, https://doi.org/10.5194/gmd-15-7471-2022, 2022
Short summary
Short summary
Pure trajectory-based transport models driven by meteorology derived from reanalysis products (ERA5) take into account only the resolved, advective part of transport. That means neither mixing processes nor unresolved subgrid-scale advective processes like convection are included. The Chemical Lagrangian Model of the Stratosphere (CLaMS) includes these processes. We show that isentropic mixing dominates unresolved transport. The second most important transport process is unresolved convection.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
Short summary
Short summary
This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Yongbo Zhou, Yubao Liu, Zhaoyang Huo, and Yang Li
Geosci. Model Dev., 15, 7397–7420, https://doi.org/10.5194/gmd-15-7397-2022, https://doi.org/10.5194/gmd-15-7397-2022, 2022
Short summary
Short summary
The study evaluates the performance of the Data Assimilation Research Testbed (DART), equipped with the recently added forward operator Radiative Transfer for TOVS (RTTOV), in assimilating FY-4A visible images into the Weather Research and Forecasting (WRF) model. The ability of the WRF-DART/RTTOV system to improve the forecasting skills for a tropical storm over East Asia and the Western Pacific is demonstrated in an Observing System Simulation Experiment framework.
Dánnell Quesada-Chacón, Klemens Barfus, and Christian Bernhofer
Geosci. Model Dev., 15, 7353–7370, https://doi.org/10.5194/gmd-15-7353-2022, https://doi.org/10.5194/gmd-15-7353-2022, 2022
Short summary
Short summary
We improved the performance of past perfect prognosis statistical downscaling methods while achieving full model repeatability with GPU-calculated deep learning models using the TensorFlow, climate4R, and VALUE frameworks. We employed the ERA5 reanalysis as predictors and ReKIS (eastern Ore Mountains, Germany, 1 km resolution) as precipitation predictand, while incorporating modern deep learning architectures. The achieved repeatability is key to accomplish further milestones with deep learning.
Mike Bush, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Aravindakshan Jayakumar, Huw Lewis, Adrian Lock, Marion Mittermaier, Saji Mohandas, Rachel North, Aurore Porson, Belinda Roux, Stuart Webster, and Mark Weeks
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-209, https://doi.org/10.5194/gmd-2022-209, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
Building on the baseline of RAL1, the RAL2 science configuration is used for regional modelling around the UM Partnership and in operations at the Met Office. RAL2 has been tested in different parts of the world including Australia, India and the U.K. RAL2 increases medium and low cloud amounts in the mid-latitudes compared to RAL1, leading to improved cloud forecasts and a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates.
Petri Clusius, Carlton Xavier, Lukas Pichelstorfer, Putian Zhou, Tinja Olenius, Pontus Roldin, and Michael Boy
Geosci. Model Dev., 15, 7257–7286, https://doi.org/10.5194/gmd-15-7257-2022, https://doi.org/10.5194/gmd-15-7257-2022, 2022
Short summary
Short summary
Atmospheric chemistry and aerosol processes form a dynamic and sensitively balanced system, and solving problems regarding air quality or climate requires detailed modelling and coupling of the processes. The models involved are often very complex to use. We have addressed this problem with the new ARCA box model. It puts much of the current knowledge of the nano- and microscale aerosol dynamics and chemistry into usable software and has the potential to become a valuable tool in the community.
Adam Milsom, Amy Lees, Adam M. Squires, and Christian Pfrang
Geosci. Model Dev., 15, 7139–7151, https://doi.org/10.5194/gmd-15-7139-2022, https://doi.org/10.5194/gmd-15-7139-2022, 2022
Short summary
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.
Johan F. de Haan, Ping Wang, Maarten Sneep, J. Pepijn Veefkind, and Piet Stammes
Geosci. Model Dev., 15, 7031–7050, https://doi.org/10.5194/gmd-15-7031-2022, https://doi.org/10.5194/gmd-15-7031-2022, 2022
Short summary
Short summary
We present an overview of the DISAMAR radiative transfer code, highlighting the novel semi-analytical derivatives for the doubling–adding formulae and the new DISMAS technique for weak absorbers. DISAMAR includes forward simulations and retrievals for satellite spectral measurements from 270 to 2400 nm to determine instrument specifications for passive remote sensing. It has been used in various Sentinel-4/5P/5 projects and in the TROPOMI aerosol layer height and ozone profile products.
Ivette H. Banos, Will D. Mayfield, Guoqing Ge, Luiz F. Sapucci, Jacob R. Carley, and Louisa Nance
Geosci. Model Dev., 15, 6891–6917, https://doi.org/10.5194/gmd-15-6891-2022, https://doi.org/10.5194/gmd-15-6891-2022, 2022
Short summary
Short summary
A prototype data assimilation system for NOAA’s next-generation rapidly updated, convection-allowing forecast system, or Rapid Refresh Forecast System (RRFS) v0.1, is tested and evaluated. The impact of using data assimilation with a convective storm case study is examined. Although the convection in RRFS tends to be overestimated in intensity and underestimated in extent, the use of data assimilation proves to be crucial to improve short-term forecasts of storms and precipitation.
Andrew Geiss, Sam J. Silva, and Joseph C. Hardin
Geosci. Model Dev., 15, 6677–6694, https://doi.org/10.5194/gmd-15-6677-2022, https://doi.org/10.5194/gmd-15-6677-2022, 2022
Short summary
Short summary
This work demonstrates the use of modern machine learning techniques to enhance the resolution of atmospheric chemistry simulations. We evaluate the schemes for an 8 x 10 increase in resolution and find that they perform substantially better than conventional methods. Methods are introduced to target machine learning methods towards this type of problem, most notably by ensuring they do not break known physical constraints.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-168, https://doi.org/10.5194/gmd-2022-168, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
When radionuclides are released into the atmosphere, the assessment of the consequences depends on the evaluation of the magnitude and temporal evolution of the release, which can be highly variable as in the case of Fukushima-Daiichi. In this paper, we propose Bayesian inverse modelling methods and the Reversible-Jump Markov Chain Monte Carlo technique, which allows to evaluate the temporal variability of the release and to integrate different types of information in the source reconstruction.
Marine Bonazzola, Hélène Chepfer, Po-Lun Ma, Johannes Quaas, David M. Winker, Artem Feofilov, and Nick Schutgens
EGUsphere, https://doi.org/10.5194/egusphere-2022-438, https://doi.org/10.5194/egusphere-2022-438, 2022
Short summary
Short summary
Aerosols have a large impact on climate. Using a lidar aerosol simulator ensures consistent comparisons between modeled and observed aerosols. In the current study, we present a lidar aerosol simulator that applies a cloud masking and an aerosol detection threshold. We estimate the lidar signals that would be observed at 532 nm by the lidar CALIOP overflying the atmosphere predicted by a climate model. Our comparison at the seasonal timescale shows a discrepancy in the Southern Hemisphere.
Daniel C. Anderson, Melanie B. Follette-Cook, Sarah A. Strode, Julie M. Nicely, Junhua Liu, Peter D. Ivatt, and Bryan N. Duncan
Geosci. Model Dev., 15, 6341–6358, https://doi.org/10.5194/gmd-15-6341-2022, https://doi.org/10.5194/gmd-15-6341-2022, 2022
Short summary
Short summary
The hydroxyl radical (OH) is the most important chemical in the atmosphere for removing certain pollutants, including methane, the second-most-important greenhouse gas. We present a methodology to create an easily modifiable parameterization that can calculate OH concentrations in a computationally efficient way. The parameterization, which predicts OH within 5 %, can be integrated into larger climate models to allow for calculation of the interactions between OH, methane, and other chemicals.
Akshay Sridhar, Yassine Tissaoui, Simone Marras, Zhaoyi Shen, Charles Kawczynski, Simon Byrne, Kiran Pamnany, Maciej Waruszewski, Thomas H. Gibson, Jeremy E. Kozdon, Valentin Churavy, Lucas C. Wilcox, Francis X. Giraldo, and Tapio Schneider
Geosci. Model Dev., 15, 6259–6284, https://doi.org/10.5194/gmd-15-6259-2022, https://doi.org/10.5194/gmd-15-6259-2022, 2022
Short summary
Short summary
ClimateMachine is a new open-source Julia-language atmospheric modeling code. We describe its limited-area configuration and the model equations, and we demonstrate applicability through benchmark problems, including atmospheric flow in the shallow cumulus regime. We show that the discontinuous Galerkin numerics and model equations allow global conservation of key variables (up to sources and sinks). We assess CPU strong scaling and GPU weak scaling to show its suitability for large simulations.
Joshua Chun Kwang Lee, Javier Amezcua, and Ross Noel Bannister
Geosci. Model Dev., 15, 6197–6219, https://doi.org/10.5194/gmd-15-6197-2022, https://doi.org/10.5194/gmd-15-6197-2022, 2022
Short summary
Short summary
In this article, we implement a novel data assimilation method for the ABC–DA system which combines traditional data assimilation approaches in a hybrid approach. We document the technical development and test the hybrid approach in idealised experiments within a tropical framework of the ABC–DA system. Our findings indicate that the hybrid approach outperforms individual traditional approaches. Its potential benefits have been highlighted and should be explored further within this framework.
Vincent Huijnen, Philippe Le Sager, Marcus O. Köhler, Glenn Carver, Samuel Rémy, Johannes Flemming, Simon Chabrillat, Quentin Errera, and Twan van Noije
Geosci. Model Dev., 15, 6221–6241, https://doi.org/10.5194/gmd-15-6221-2022, https://doi.org/10.5194/gmd-15-6221-2022, 2022
Short summary
Short summary
We report on the first implementation of atmospheric chemistry and aerosol as part of the OpenIFS model, based on the CAMS global model. We give an overview of the model and evaluate two reference model configurations, with and without the stratospheric chemistry extension, against a variety of observational datasets. This OpenIFS version with atmospheric composition components is open to the scientific user community under a standard OpenIFS license.
Xueyin Ruan, Chun Zhao, Rahul A. Zaveri, Pengzhen He, Xinming Wang, Jingyuan Shao, and Lei Geng
Geosci. Model Dev., 15, 6143–6164, https://doi.org/10.5194/gmd-15-6143-2022, https://doi.org/10.5194/gmd-15-6143-2022, 2022
Short summary
Short summary
Accurate prediction of aerosol pH in chemical transport models is essential to aerosol modeling. This study examines the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) on aerosol pH predictions and the sensitivities to emissions of nonvolatile cations and NH3, aerosol-phase state assumption, and heterogeneous sulfate production. Temporal evolution of aerosol pH during haze cycles in Beijing and the driving factors are also presented and discussed.
Adrian Rojas-Campos, Michael Langguth, Martin Wittenbrink, and Gordon Pipa
EGUsphere, https://doi.org/10.5194/egusphere-2022-648, https://doi.org/10.5194/egusphere-2022-648, 2022
Short summary
Short summary
Our manuscript presents an alternative approach for generating high-resolution precipitation maps based on the non-linear combination of the complete set of variables of the numerical weather predictions. This process combines the super-resolution task with the bias correction in a single step, generating high-resolution corrected precipitation maps with 3 hour lead time. We used using deep learning algorithms to combine the input information and increase the accuracy of the precipitation maps.
Ping Wang, Kebiao Mao, Fei Meng, Zhihao Qin, Shu Fang, and Sayed M. Bateni
Geosci. Model Dev., 15, 6059–6083, https://doi.org/10.5194/gmd-15-6059-2022, https://doi.org/10.5194/gmd-15-6059-2022, 2022
Short summary
Short summary
In order to obtain the key parameters of high-temperature spatial–temporal variation analysis, this study proposed a daily highest air temperature (Tmax) estimation frame to build a Tmax dataset in China from 1979 to 2018. We found that the annual and seasonal mean Tmax in most areas of China showed an increasing trend. The abnormal temperature changes mainly occurred in El Nin~o years or La Nin~a years. IOBW had a stronger influence on China's warming events than other factors.
Cited articles
Abdul-Razzak, H. and Ghan, S.: A parameterization of aerosol activation, 2. Multiple aerosol types, J. Geophys. Res., 105, 6837–6844, https://doi.org/10.1029/1999JD901161, 2000.
Arakawa, A.: The cumulus parameterization problem: Past, present, and future, J. Climate, 17, 2493–2525, 2004.
Bacmeister, J., Eckermann, S., Tsias, A., Carslaw, K., and Peter, T.: Mesoscale temperature fluctuations induced by a spectrum of gravity waves: A comparison of parameterizations and their impact on stratospheric microphysics, J. Atmos. Sci., 56, 1913–1924, 1999.
Bacmeister, J., Suarez, M., and Robertson, F. R.: Rain Reevaporation, Boundary Layer, Convection Interactions, and Pacific Rainfall Patterns in an AGCM, J. Atmos. Sci., 63, 3383–3403, https://doi.org/10.1175/JAS3791.1, 2006.
Baker, B. A.: On the Role of Phoresis in Cloud Ice Initiation, J. Atmos. Sci., 48, 1545–1548, https://doi.org/10.1175/1520-0469(1991)048<1545:OTROPI>2.0.CO;2, 1991.
Barahona, D.: On the ice nucleation spectrum, Atmos. Chem. Phys., 12, 3733–3752, https://doi.org/10.5194/acp-12-3733-2012, 2012.
Barahona, D. and Nenes, A.: Parameterization of cloud droplet formation in large scale models: including effects of entrainment, J. Geophys. Res., 112, D16026, https://doi.org/10.1029/2007JD008473, 2007.
Barahona, D. and Nenes, A.: Parameterization of cirrus formation in large scale models: Homogeneous nucleation, J. Geophys. Res., 113, D11211, https://doi.org/10.1029/2007JD009355, 2008.
Barahona, D. and Nenes, A.: Parameterizing the competition between homogeneous and heterogeneous freezing in cirrus cloud formation – monodisperse ice nuclei, Atmos. Chem. Phys., 9, 369–381, https://doi.org/10.5194/acp-9-369-2009, 2009a.
Barahona, D. and Nenes, A.: Parameterizing the competition between homogeneous and heterogeneous freezing in cirrus cloud formation – monodisperse ice nuclei, Atmos. Chem. Phys., 9, 369–381, https://doi.org/10.5194/acp-9-369-2009, 2009b.
Barahona, D. and Nenes, A.: Dynamical states of low temperature cirrus, Atmos. Chem. Phys., 11, 3757–3771, https://doi.org/10.5194/acp-11-3757-2011, 2011.
Barahona, D., Rodriguez, J., and Nenes, A.: Sensitivity of the global distribution of cirrus Ice crystal concentration to heterogeneous freezing, J. Geophys. Res., 15, D23213, https://doi.org/10.1029/2010JD014273, 2010a.
Barahona, D., West, R. E. L., Stier, P., Romakkaniemi, S., Kokkola, H., and Nenes, A.: Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations, Atmos. Chem. Phys., 10, 2467–2473, https://doi.org/10.5194/acp-10-2467-2010, 2010b.
Barkstrom, B.: The earth radiation budget experiment (ERBE), B. Am. Meteorol. Soc., 65, 1170–1185, 1984.
Blackadar, A. K.: The Vertical Distribution of Wind and Turbulent Exchange in a Neutral Atmosphere, J. Geophys. Res., 67, 3095–3102, 1962.
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L., Klein, S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John, V. O.: COSP: Satellite simulation software for model assessment, B. Am. Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011.
Burrows, S. M., Hoose, C., Pöschl, U., and Lawrence, M. G.: Ice nuclei in marine air: biogenic particles or dust?, Atmos. Chem. Phys., 13, 245–267, https://doi.org/10.5194/acp-13-245-2013, 2013.
Chiriaco, M., Chepfer, H., Minnis, P., Haeffelin, M., Platnick, S., Baumgardner, D., Dubuisson, P., McGill, M., Noël, V., Pelon, J., Spangenberg, D., Sun-Mack, S., and Wind, G.: Comparison of CALIPSO-like, LaRC, and MODIS retrievals of ice-cloud properties over SIRTA in France and Florida during CRYSTAL-FACE, J. Appl. Meteorol. Clim., 46, 249–272, 2007.
Choi, Y., Lindzen, R., Ho, C., and Kim, J.: Space observations of cold-cloud phase change, P. Natl. Acad. Sci., 107, 11211–11216, 2010.
Chou, M.-D. and Suarez, M.: An efficient thermal infrared radiation parameterization for use in general circulation models, Vol. 3 of NASA Tech. Memorandum 104606, NASA Goddard Space Flight Center, Greenbelt, MD, USA, 1994.
Chou, M.-D., Suarez, M., Ho, C.-H., Yan, M.-H., and Lee, K.-T.: A Solar Radiation Model for Use in Climate Studies, J. Atmos. Sci., 49, 762–772, 1992.
Colarco, P., da Silva, A., Chin, M., and Diehl, T.: Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth, J. Geophys. Res., 115, D14207, https://doi.org/10.1029/2009JD012820, 2010.
Conant, W. C., VanReken, T., Rissman, T., Varutbangkul, V., Jonsson, H., Nenes, A., Jimenez, J., Delia, A., Bahreini, R., Roberts, G., Flagan, R., and Seinfeld, J. H.: Aerosol-cloud drop concentration closure in warm clouds, J. Geophys. Res., 109, D13204, https://doi.org/10.1029/2003JD004324, 2004.
Cziczo, D. J., Froyd, K. D., Hoose, C., Jensen, E. J., Diao, M., Zondlo, M. A., Smith, J. B., Twohy, C. H., and Murphy, D. M.: Clarifying the Dominant Sources and Mechanisms of Cirrus Cloud Formation, Science, 340, 1320–1324, 2013.
Dean, S. M., Flowerdew, J., Lawrence, B. N., and Eckermann, S. D.: Parameterisation of orographic cloud dynamics in a GCM, Clim. Dynam., 28, 581–597, https://doi.org/10.1007/s00382-006-0202-0, 2007.
Del Genio, A., Yao, M., Kovari, W., and Lo, K.: A prognostic cloud water parameterization for global climate models, J. Climate, 9, 270–304, 1996.
Del Genio, A. D., Kovari, W., Yao, M.-S., and Jonas, J.: Cumulus Microphysics and Climate Sensitivity, J. Climate, 18, 2376–2387, https://doi.org/10.1175/JCLI3413.1, 2005.
DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D., Twohy, C. H., Richardson, M. S., Eidhammer, T., and Rogers, D. C.: Predicting global atmospheric ice nuclei distributions and their impacts on climate, P. Natl. Acad. Sci., 107, 11217–11222, https://doi.org/10.1073/pnas.0910818107, 2010.
Devasthale, A. and Thomas, M. A.: Sensitivity of Cloud Liquid Water Content Estimates to the Temperature-Dependent Thermodynamic Phase: A Global Study Using CloudSat Data, J. Climate, 25, 7297–7307, 2012.
Diehl, T., Heil, A., Chin, M., Pan, X., Streets, D., Schultz, M., and Kinne, S.: Anthropogenic, biomass burning, and volcanic emissions of black carbon, organic carbon, and SO2 from 1980 to 2010 for hindcast model experiments, Atmos. Chem. Phys. Discuss., 12, 24895–24954, https://doi.org/10.5194/acpd-12-24895-2012, 2012.
Eliasson, S., Buehler, S. A., Milz, M., Eriksson, P., and John, V. O.: Assessing observed and modelled spatial distributions of ice water path using satellite data, Atmos. Chem. Phys., 11, 375–391, https://doi.org/10.5194/acp-11-375-2011, 2011.
Ferrier, S. B.: A Double-Moment Multiple-Phase Four-Class Bulk Ice Scheme. Part I: Description, J. Atmos. Sci., 51, 249–280, https://doi.org/10.1175/1520-0469(1994)051<0249:ADMMPF>2.0.CO;2, 1994.
Fornea, A. P., Brooks, S. D., Dooley, J. B., and Saha, A.: Heterogeneous freezing of ice on atmospheric aerosols containing ash, soot, and soil, J. Geophys. Res., 114, D13201, https://doi.org/10.1029/2009JD011958, 2009.
Fountoukis, C. and Nenes, A.: Continued development of a cloud droplet formation parameterization for global climate models, J. Geophys. Res., 110, D11212, https://doi.org/10.1029/2004JD005591, 2005.
Fountoukis, C., Nenes, A., Meskhidze, N., Bahreini, R., Conant, W. C., Jonsson, H., Murphy, S., Sorooshian, A., Varutbangkul, V., Brechtel, F., Flagan, R., and Seinfeld, J. H.: Aerosol-cloud drop concentration closure for clouds sampled during the International Consortium for Atmospheric Reseach on Transport and Transformation 2004 campaign, J. Geophys. Res., 112, D10S30, https://doi.org/10.1029/2006JD007272, 2007.
Frank, W. M. and Cohen, C.: Simulation of Tropical Convective Systems. Part I: A Cumulus Parameterization, J. Atmos. Sci., 44, 3787–3799, https://doi.org/10.1175/1520-0469(1987)044<3787:SOTCSP>2.0.CO;2, 1987.
Gayet, J., Ovarlez, J., Shcherbakov, V., Ström, J., Schumann, U., Minikin, A., Auriol, F., Petzold, A., and Monier, M.: Cirrus cloud microphysical and optical properties at southern and northern midlatitudes during the INCA experiment, J. Geophys. Res., 109, D20206, https://doi.org/10.1029/2004JD004803, 2004.
Gettelman, A. and Kinnison, D. E.: The global impact of supersaturation in a coupled chemistry-climate model, Atmos. Chem. Phys., 7, 1629–1643, https://doi.org/10.5194/acp-7-1629-2007, 2007.
Gettelman, A., Fetzer, E. J., Eldering, A., and Irion, F. W.: The global distribution of supersaturation in the upper troposphere from the Atmospheric Infrared Sounder, J. Climate, 19, 6089–6103, 2006.
Gettelman, A., Morrison, H., and Ghan, S. J.: A New Two-Moment Bulk Stratiform Cloud Microphysics Scheme in the Community Atmosphere Model, Version 3 (CAM3). Part II: Single-Column and Global Results, J. Climate, 21, 3660–3679, https://doi.org/10.1175/2008JCLI2116.1, 2008.
Gettelman, A., Liu, X., Ghan, S. J., Morrison, H., Park, S., Conley, A. J., Klein, S. A., Boyle, J., Mitchell, D. L., and Li, J.-L. F.: Global simulations of ice nucleation and ice supersaturation with an improved cloud scheme in the Community Atmosphere Model, J. Geophys. Res., 115, D18216, https://doi.org/10.1029/2009JD013797, 2010.
Gettelman, A., Liu, X., Barahona, D., Lohmann, U., and Chen, C.: Climate impacts of ice nucleation, J. Geophys. Res., 117, D20201, https://doi.org/10.1029/2012JD017950, 2012.
Gierens, K., Schumann, U., Helten, M., Smit, H., and Marenco, A.: A distribution law for relative humidity in the upper troposphere and lower stratosphere derived from three years of MOZAIC measurements, Ann. Geophys., 17, 1218–1226, https://doi.org/10.1007/s00585-999-1218-7, 1999.
Golaz, J.-C., Salzmann, M., Donner, L. J., Horowitz, L. W., Ming, Y., and Zhao, M.: Sensitivity of the Aerosol Indirect Effect to Subgrid Variability in the Cloud Parameterization of the GFDL Atmosphere General Circulation Model AM3, J. Climate, 24, 3145–3160, https://doi.org/10.1175/2010JCLI3945.1, 2010.
Gregory, D.: Estimation of entrainment rate in simple models of convective clouds, Q. J. Roy. Meteorol. Soc., 127, 53–72, 2001.
Gultepe, I. and Isaac, G.: The relationship between cloud droplet and aerosol number concentrations for climate models, Int. J. Climatol., 16, 941–946, 1996.
Guo, H., Liu, Y., Daum, P., Senum, G., and Tao, W.: Characteristics of vertical velocity in marine stratocumulus: comparison of large eddy simulations with observations, Environ. Res. Lett., 3, 045020, https://doi.org/10.1088/1748-9326/3/4/045020, 2008.
Haag, W. and Kärcher, B.: The impact of aerosols and gravity waves on cirrus at midlatitudes, J. Geophys. Res., 109, D12202, https://doi.org/10.1029/2004JD004579, 2004.
Han, Q., Rossow, W. B., Chou, J., and Welch, R. M.: Global variation of column droplet concentration in low-level clouds, Geophys. Res. Lett., 25, 1419–1422, https://doi.org/10.1029/98GL01095, 1998.
Hendricks, J., Kärcher, B., and Lohmann, U.: Effects of ice nuclei on cirrus clouds in a global climate model, J. Geophys. Res., 116, D18206, https://doi.org/10.1029/2010JD015302, 2011.
Herzog, A. and Vial, F.: A study of the dynamics of the equatorial lower stratosphere by use of ultra-long-duration balloons, J. Geophys. Res., 106, 22745–22761, 2001.
Heymsfield, A. J., Bansemer, A., Field, P. R., Durden, S. L., Stith, J. L., Dye, J. E., Hall, W., and Grainger, C. A.: Observations and Parameterizations of Particle Size Distributions in Deep Tropical Cirrus and Stratiform Precipitating Clouds: Results from In Situ Observations in TRMM Field Campaigns., J. Atmos. Sci., 59, 3457–3491, https://doi.org/10.1175/1520-0469(2002)059<3457:OAPOPS>2.0.CO;2, 2002.
Heymsfield, A. J., van Zadelhoff, G.-J., Donovan, D. P., Fabry, F., Hogan, R. J., and Illingworth, A. J.: Refinements to Ice Particle Mass Dimensional and Terminal Velocity Relationships for Ice Clouds. Part II: Evaluation and Parameterizations of Ensemble Ice Particle Sedimentation Velocities, J. Atmos. Sci., 64, 1068–1088, https://doi.org/10.1175/JAS3900.1, 2007.
Hoose, C., Kristjánsson, J., and Burrows, S.: How important is biological ice nucleation in clouds on a global scale?, Environ. Res. Lett., 5, 024009, https://doi.org/10.1088/1748-9326/5/2/024009, 2010.
Hu, Y., Rodier, S., Xu, K.-M., Sun, W., Huang, J., Lin, B., Zhai, P., and Josset, D.: Occurrence, liquid water content, and fraction of supercooled water clouds from combined CALIOP/IIR/MODIS measurements, J. Geophys. Res., 115, D00H34, https://doi.org/10.1029/2009JD012384, 2010.
Huffman, G., Adler, R., Arkin, P., Chang, A., Ferraro, R., Gruber, A., Janowiak, J., McNab, A., Rudolf, B., and Schneider, U.: The global precipitation climatology project (GPCP) combined precipitation dataset, B. Am. Meteorol. Soc., 78, 5–20, 1997.
IPCC: Climate change 2007: the physical basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA., 2007.
Jensen, E. and Pfister, L.: Transport and freeze-drying in the tropical tropopause layer, J. Geophys. Res., 109, D02207, https://doi.org/10.1029/2003JD004022, 2004.
Jensen, E. J., Pfister, L., Bui, T.-P., Lawson, P., and Baumgardner, D.: Ice nucleation and cloud microphysical properties in tropical tropopause layer cirrus, Atmos. Chem. Phys., 10, 1369–1384, https://doi.org/10.5194/acp-10-1369-2010, 2010.
Jensen, E. J., Pfister, L., and Bui, T. P.: Physical processes controlling ice concentrations in cold cirrus near the tropical tropopause, J. Geophys. Res., 117, D11205, https://doi.org/10.1029/2011JD017319, 2012.
Joos, H., Spichtinger, P., Gayet, J., and Minikin, A.: Orographic cirrus in the global climate model ECHAM5, J. Geophys. Res., 113, https://doi.org/10.1029/2007JD009605, 2008.
Joos, H., Spichtinger, P., and Lohmann, U.: Influence of a future climate on the microphysical and optical properties of orographic cirrus clouds in ECHAM5, J. Geophys. Res., 115, D19129, https://doi.org/10.1029/2010JD013824, 2010.
Kärcher, B. and Burkhardt, U.: A cirrus scheme for global circulation models, Q. J. Roy. Meteorol. Soc., 134, 1439–1461, https://doi.org/10.1002/Qj.301, 2008.
Kärcher, B. and Lohmann, U.: A parameterization of cirrus cloud formation: homogeneous freezing including effects or aerosol size, J. Geophys. Res., 107, 4698, https://doi.org/10.1029/2001JD001429, 2002.
Kärcher, B. and Ström, J.: The roles of dynamical variability and aerosols in cirrus cloud formation, Atmos. Chem. Phys., 3, 823–838, https://doi.org/10.5194/acp-3-823-2003, 2003.
Kärcher, B., Hendricks, J., and Lohmann, U.: Physically based parameterization of cirrus cloud formation for use in global atmospheric models, J. Geophys. Res., 111, D01205, https://doi.org/10.1029/2005JD006219, 2006.
Kaufman, Y. J. and Koren, I.: Smoke and pollution aerosol effect on cloud cover, Science, 313, 655–658, 2006.
Kay, J., Hillman, B., Klein, S., Zhang, Y., Medeiros, B., Pincus, R., Gettelman, A., Eaton, B., Boyle, J., Marchand, R., and Ackerman, A.: Exposing global cloud biases in the Community Atmosphere Model (CAM) using satellite observations and their corresponding instrument simulators, J. Climate, 25, 5190–5207, 2012.
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, https://doi.org/10.1016/S0169-8095(00)00064-8, 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.
King, M., Menzel, W., Kaufman, Y., Tanre, D., Gao, B.-C., Platnick, S., Ackerman, S., Remer, L., Pincus, R., and Hubanks, P.: Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS, IEEE T. Geosci. Remote, 41, 442–458, https://doi.org/10.1109/TGRS.2002.808226, 2003.
Koop, T., Luo, B., Tslas, A., and Peter, T.: Water activity as the determinant for homogeneous ice nucleation in aqueous solutions, Nature, 406, 611–614, 2000.
Korolev, A. and Mazin, I.: Supersaturation of water vapor in clouds, J. Atmos. Sci., 60, 2957–2974, 2003.
Krämer, M., Schiller, C., Afchine, A., Bauer, R., Gensch, I., Mangold, A., Schlicht, S., Spelten, N., Sitnikov, N., Borrmann, S., de Reus, M., and Spichtinger, P.: Ice supersaturations and cirrus cloud crystal numbers, Atmos. Chem. Phys., 9, 3505–3522, https://doi.org/10.5194/acp-9-3505-2009, 2009.
Kumar, P., Nenes, A., and Sokolik, I. N.: Importance of adsorption for CCN activity and hygroscopic properties of mineral dust aerosol, Geophys. Res. Lett., 36, L24804, https://doi.org/10.1029/2009GL040827, 2009a.
Kumar, P., Sokolik, I. N., and Nenes, A.: Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN, Atmos. Chem. Phys., 9, 2517–2532, https://doi.org/10.5194/acp-9-2517-2009, 2009b.
Ladino, L., Stetzer, O., Lüönd, F., Welti, A., and Lohmann, U.: Contact freezing experiments of kaolinite particles with cloud droplets, J. Geophys. Res., 116, D22202, https://doi.org/10.1029/2011JD015727, 2011.
Lance, S., Nenes, A., and Rissman, T.: Chemical and dynamical effects on cloud droplet number: Implication for estimates of the aerosol indirect effect, J. Geophys. Res., 109, D22208, https://doi.org/10.1029/2004JD004596, 2004.
Lance, S., Shupe, M. D., Feingold, G., Brock, C. A., Cozic, J., Holloway, J. S., Moore, R. H., Nenes, A., Schwarz, J. P., Spackman, J. R., Froyd, K. D., Murphy, D. M., Brioude, J., Cooper, O. R., Stohl, A., and Burkhart, J. F.: Cloud condensation nuclei as a modulator of ice processes in Arctic mixed-phase clouds, Atmos. Chem. Phys., 11, 8003–8015, https://doi.org/10.5194/acp-11-8003-2011, 2011.
Li, J.-L. F., Waliser, D. E., Chen, W.-T., Guan, B., Kubar, T., Stephens, G., Ma, H.-Y., Deng, M., Donner, L., Seman, C., and Horowitz, L.: An observationally based evaluation of cloud ice water in CMIP3 and CMIP5 GCMs and contemporary reanalyses using contemporary satellite data, J. Geophys. Res., 117, D16105, https://doi.org/10.1029/2012JD017640, 2012.
Li, J.-L. F., Lee, S., Waliser, D. E., Lee, S., Guan, B., Stephens, G., and Teixeira, J.: Assessment of Cloud Liquid Water in CMIP3, CMIP5, and Contemporary GCMs and Reanalyses with Observations, J. Geophys. Res., under review, 2014.
Lindzen, R. S.: Turbulence and stress owing to gravity wave and tidal breakdown, J. Geophys. Res., 86, 9707–9714, https://doi.org/10.1029/JC086iC10p09707, 1981.
Liu, X., Shi, X., Zhang, K., Jensen, E. J., Gettelman, A., Barahona, D., Nenes, A., and Lawson, P.: Sensitivity studies of dust ice nuclei effect on cirrus clouds with the Community Atmosphere Model CAM5, Atmos. Chem. Phys., 12, 12061–12079, https://doi.org/10.5194/acp-12-12061-2012, 2012.
Liu, Y., Daum, P., and Yum, S.: Analytical expression for the relative dispersion of the cloud droplet size distribution, Geophys. Res. Lett., 33, L02810, https://doi.org/10.1029/2005GL024052, 2006.
Liu, Y., Daum, P., Guo, H., and Peng, Y.: Dispersion bias, dispersion effect, and the aerosol-cloud conundrum, Environ. Res. Lett., 3, 045021, https://doi.org/10.1088/1748-9326/3/4/045021, 2008.
Locatelli, J. D. and Hobbs, P. V.: Fall Speeds and Masses of Solid Precipitation Particles, J. Geophys. Res., 79, 2185–2197, https://doi.org/10.1029/JC079i015p02185, 1974.
Loeb, N., Wielicki, B., Doelling, D., Smith, G., Keyes, D., Kato, S., Manalo-Smith, N., and Wong, T.: Toward optimal closure of the Earth's top-of-atmosphere radiation budget, J. Climate, 22, 748–766, 2009.
Lohmann, U.: Global anthropogenic aerosol effects on convective clouds in ECHAM5-HAM, Atmos. Chem. Phys., 8, 2115-2131, https://doi.org/10.5194/acp-8-2115-2008, 2008.
Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review, Atmos. Chem. Phys., 5, 715–737, https://doi.org/10.5194/acp-5-715-2005, 2005.
Lohmann, U., Spichtinger, P., Jess, S., Peter, T., and Smit, H.: Cirrus cloud formation and ice supersaturated regions in a global climate model, Environ. Res. Lett., 3, 045022; https://doi.org/10.1088/1748-9326/3/4/045022, 2008.
Louis, J. F., Weill, A., and Vidal-Madjar, D.: Dissipation length in stable layers, Bound.-La. Meteorol., 25, 229–243, https://doi.org/10.1007/BF00119538, 1983.
Manabe, S., Smagorinsky, J., and Strickler, R. F.: Simulated climatology of a general circulation model with a hydrologic cycle 1, Mon. Weather Rev., 93, 769–798, 1965.
Marcolli, C., Gedamke, S., Peter, T., and Zobrist, B.: Efficiency of immersion mode ice nucleation on surrogates of mineral dust, Atmos. Chem. Phys., 7, 5081–5091, https://doi.org/10.5194/acp-7-5081-2007, 2007.
Marshall, J. S. and Palmer, W. M. K.: The distribution of raindrops with size, J. Meteorol., 5, 165–166, 1948.
McFarlane, N. A.: The Effect of Orographically Excited Gravity Wave Drag on the General Circulation of the Lower Stratosphere and Troposphere, J. Atmos. Sci., 44, 1775–1800, https://doi.org/10.1175/1520-0469(1987)044<1775:TEOOEG>2.0.CO;2, 1987.
McFarquhar, G. and Heymsfield, A.: Parameterization of tropical cirrus ice crystal size distributions and implications for radiative transfer: Results from CEPEX, J. Atmos. Sci., 54, 2187–2200, 1997.
Molod, A.: Constraints on the Total Water PDF in GCMs from AIRS and a High Resolution Model, J. Climate, 25, 8341–8352, 2012.
Molod, A., Takacs, L., Suarez, M., Bacmeister, J., Song, I., and Eichmann, A.: The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna, Vol. 28 of Technical Report Series on Global Modeling and Data Assimilation, NASA Goddard Space Flight Center, Greenbelt, MD, USA, 2012.
Moorthi, S. and Suarez, M. J.: Relaxed Arakawa-Schubert – A parameterization of moist convection for general circulation models, Mon. Weather Rev., 120, 978–1002, 1992.
Morales, R. and Nenes, A.: Characteristic updrafts for computing distribution-averaged cloud droplet number, and stratocumulus cloud properties, J. Geophys. Res., 115, D18220, https://doi.org/10.1029/2009JD013233, 2010.
Morales Betancourt, R., Lee, D., Oreopoulos, L., Sud, Y. C., Barahona, D., and Nenes, A.: Sensitivity of cirrus and mixed-phase clouds to the ice nuclei spectra in McRAS-AC: single column model simulations, Atmos. Chem. Phys., 12, 10679–10692, https://doi.org/10.5194/acp-12-10679-2012, 2012.
Morrison, H. and Gettelman, A.: A New Two-Moment Bulk Stratiform Cloud Microphysics Scheme in the Community Atmosphere Model, Version 3 (CAM3). Part I: Description and Numerical Tests, J. Climate, 21, 3642–3659, https://doi.org/10.1175/2008JCLI2105.1, 2008.
Morrison, H., Curry, J. A., and Khvorostyanov, V. I.: A New Double-Moment Microphysics Parameterization for Application in Cloud and Climate Models. Part I: Description, J. Atmos. Sci., 62, 1665–1677, https://doi.org/10.1175/JAS3446.1, 2005.
Morrison, H., de Boer, G., Feingold, G., Harrington, J., Shupe, M. D., and Sulia, K.: Resilience of persistent Arctic mixed-phase clouds, Nat. Geosci., 5, 11–17, https://doi.org/10.1038/ngeo1332, 2012.
Murray, B. J., Broadley, S. L., Wilson, T. W., Atkinson, J. D., and Wills, R. H.: Heterogeneous freezing of water droplets containing kaolinite particles, Atmos. Chem. Phys., 11, 4191–4207, https://doi.org/10.5194/acp-11-4191-2011, 2011.
Murray, B. J., OSullivan, D., Atkinson, J., and Webb, M.: Ice nucleation by particles immersed in supercooled cloud droplets, Chem. Soc. Rev., 41, 6519–6554, 2012.
Nenes, A. and Seinfeld, J. H.: Parameterization of cloud droplet formation in global climate models, J. Geophys. Res., 108, 4415, https://doi.org/10.1029/2002JD002911, 2003.
Niemand, M., Möhler, O., Vogel, B., Vogel, H., Hoose, C., Connolly, P., Klein, H., Bingemer, H., DeMott, P., Skrotzki, J., and Leisner, T.: A particle-surface-area-based parameterization of immersion freezing on desert dust particles, J. Atmos. Sci., 69, 3077–3092, https://doi.org/10.1175/JAS-D-11-0249.1, 2012.
Peng, Y., Lohmann, U., and Leaitch, W.: Importance of vertical velocity variations in the cloud droplet nucleation process of marine stratocumulus, J. Geophys. Res., 110, D21213, https://doi.org/10.1029/2004JD004922, 2005.
Petters, M. D. and Kreidenweis, S. M.: A single parameter representation of hygroscopic growth and cloud condensation nucleus activity, Atmos. Chem. Phys., 7, 1961–1971, https://doi.org/10.5194/acp-7-1961-2007, 2007.
Phillips, V. T., Donner, L., and Garner, S.: Nucleation processes in deep convection simulated by a cloud-system-resolving model with double-moment bulk microphysics, J. Atmos. Sci., 64, 738–761, https://doi.org/10.1175/JAS3869.1, 2007.
Phillips, V. T., DeMott, P., and Andronache, C.: An empirical parameterization of heterogeneous ice nucleation for multiple chemical species of aerosol, J. Atmos. Sci., 65, 2757–2783, https://doi.org/10.1175/2007JAS2546.1, 2008.
Phillips, V. T., Demott, P. J., Andronache, C., Pratt, K. A., Prather, K. A., Subramanian, R., and Twohy, C.: Improvements to an Empirical Parameterization of Heterogeneous Ice Nucleation and its Comparison with Observations, J. Atmos. Sci., 70, 378–409, https://doi.org/10.1175/JAS-D-12-080.1, 2013.
Pincus, R., Platnick, S., Ackerman, S., Hemler, R., and Patrick Hofmann, R.: Reconciling simulated and observed views of clouds: MODIS, ISCCP, and the limits of instrument simulators, J. Climate, 25, 4699–4720, 2012.
Platnick, S., King, M., Ackerman, S., Menzel, W., Baum, B., Riédi, J., and Frey, R.: The MODIS cloud products: Algorithms and examples from Terra, IEEE T. Geosci. Remote., 41, 459–473, 2003.
Popovitcheva, O., Kireeva, E., Persiantseva, N., Khokhlova, T., Shonija, N., Tishkova, V., and Demirdjian, B.: Effect of soot on immersion freezing of water and possible atmospheric implications, Atmos. Res., 90, 326–337, 2008.
Pruppacher, H. and Klett, J.: Microphysics of clouds and precipitation, Kluwer Academic Publishers, Boston, MA, 2nd Edn., 1997.
Putman, W. and Suarez, M.: Cloud-system resolving simulations with the NASA Goddard Earth Observing System global atmospheric model (GEOS-5), Geophys. Res. Lett., 38, L16809, https://doi.org/10.1029/2011GL048438, 2011.
Quaas, J., Ming, Y., Menon, S., Takemura, T., Wang, M., Penner, J. E., Gettelman, A., Lohmann, U., Bellouin, N., Boucher, O., Sayer, A. M., Thomas, G. E., McComiskey, A., Feingold, G., Hoose, C., Kristjánsson, J. E., Liu, X., Balkanski, Y., Donner, L. J., Ginoux, P. A., Stier, P., Grandey, B., Feichter, J., Sednev, I., Bauer, S. E., Koch, D., Grainger, R. G., Kirkevåg, A., Iversen, T., Seland, Ø., Easter, R., Ghan, S. J., Rasch, P. J., Morrison, H., Lamarque, J.-F., Iacono, M. J., Kinne, S., and Schulz, M.: Aerosol indirect effects – general circulation model intercomparison and evaluation with satellite data, Atmos. Chem. Phys., 9, 8697–8717, https://doi.org/10.5194/acp-9-8697-2009, 2009.
Raatikainen, T., Nenes, A., Seinfeld, J. H., Morales, R., Moore, R. H., Lathem, T. L., Lance, S., Padro, L. T., Lin, J. J., Cerully, K. M., Bougiatioti, A., Cozic, J., Ruehl, C. R., Chuang, P. Y., Anderson, B. E., Flagan, R. C., Jonsson, H., Mihalopoulos, N., and Smith, J. N.: Worldwide data sets constrain the water vapor uptake coefficient in cloud formation, P. Natl. Acad. Sci., 110, 3760–3764, https://doi.org/10.1073/pnas.1219591110, 2013.
Ramanathan, V., Crutzen, P., Kiehl, J., and Rosenfeld, D.: Aerosols, climate, and the hydrological cycle, Science, 294, 2119–2124, 2001.
Reale, O., Lau, W. K., Kim, K.-M., and Brin, E.: Atlantic Tropical Cyclogenetic Processes during SOP-3 NAMMA in the GEOS-5 Global Data Assimilation and Forecast System, J. Atmos. Sci., 66, 3563–3578, https://doi.org/10.1175/2009JAS3123.1, 2009.
Ren, C. and Mackenzie, A.: Cirrus parameterization and the role of ice nuclei, Q. J. Roy. Meteorol. Soc., 131, 1585–1605, 2005.
Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W.: An Improved In Situ and Satellite SST Analysis for Climate, J. Climate, 15, 1609–1625, https://doi.org/10.1175/1520-0442(2002)015<1609:AIISAS>2.0.CO;2, 2002.
Rienecker, M., Suarez, M., Todling, R., Bacmeister, J., Takacs, L., Liu, H.-C., Gu, W., Sienkiewicz, M., Koster, R., Gelaro, R., Stajner, I., and Nielsen, J.: The GEOS-5 Data Assimilation System – Documentation of Versions 5.0.1, 5.1.0, and 5.2.0., Vol. 27 of Technical Report Series on Global Modeling and Data Assimilation, NASA Goddard Space Flight Center, Greenbelt, MD, USA, 2008.
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G.-K., Bloom, S., Chen, J., Collins, D., Conaty, A., da Silva, A., Gu, W., Joiner, J., Koster, R. D., Lucchesi, R., Molod, A., Owens, T., Pawson, S., Pegion, P., Redder, C. R., Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and Woollen, J.: MERRA: NASA's Modern-Era Retrospective Analysis for Research and Applications, J. Climate, 24, 3624–3648, https://doi.org/10.1175/JCLI-D-11-00015.1, 2011.
Rosenfeld, D. and Woodley, W. L.: Deep convective clouds with sustained supercooled liquid water down to −37.5 °C, Nature, 405, 440–442, https://doi.org/10.1038/35013030, 2000.
Rosenfeld, D., Lohmann, U., Raga, G. B., O'Dowd, C. D., Kulmala, M., Fuzzi, S., Reissell, A., and Andreae, M. O.: Flood or Drought: How Do Aerosols Affect Precipitation?, Science, 321, 1309–1313, https://doi.org/10.1126/science.1160606, 2008.
Rossow, W. and Schiffer, R.: Advances in understanding clouds from ISCCP, B. Am. Meteorol. Soc., 80, 2266–2288, 1999.
Salzmann, M., Ming, Y., Golaz, J.-C., Ginoux, P. A., Morrison, H., Gettelman, A., Krämer, M., and Donner, L. J.: Two-moment bulk stratiform cloud microphysics in the GFDL AM3 GCM: description, evaluation, and sensitivity tests, Atmos. Chem. Phys., 10, 8037–8064, https://doi.org/10.5194/acp-10-8037-2010, 2010.
Sato, K.: Vertical wind disturbances in the troposphere and lower stratosphere observed by the MU radar, J. Atmos. Sci., 47, 2803–2817, 1990.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics, John Wiley and Sons, New York, NY, USA, 1998.
Slingo, J.: The development and verification of a cloud prediction scheme for the ECMWF model, Q. J. R. Meteorol. Soc., 113, 899–927, 1987.
Smith, R. N. B.: A scheme for predicting layer clouds and their water content in a general circulation model, Q. J. Roy. Meteorol. Soc., 116, 435–460, 1990.
Song, X. and Zhang, G. J.: Microphysics parameterization for convective clouds in a global climate model: Description and single-column model tests, J. Geophys. Res., 116, D02201, https://doi.org/10.1029/2010JD014833, 2011.
Spencer, R., Hood, R., and Goodman, H.: Precipitation retrieval over land and ocean with the SSM/I-Identification and characteristics of the scattering signal, J. Atm. Ocean. Tech., 6, 254–273, 1989.
Spichtinger, P. and Cziczo, D. J.: Impact of heterogeneous ice nuclei on homogeneous freezing events in cirrus clouds, J. Geophys. Res., 115, D14208, https://doi.org/10.1029/2009JD012168, 2010.
Stevens, B. and Feingold, G.: Untangling aerosol effects on clouds and precipitation in a buffered system, Nature, 461, 607–613, 2009.
Sud, Y. C. and Walker, G. K.: Microphysics of clouds with the relaxed Arakawa Schubert scheme (McRAS). Part I: Design and evaluation with GATE Phase III Data, J. Atmos. Sci., 56, 3196–3220, https://doi.org/10.1175/1520-0469(1999)056<3196:MOCWTR>2.0.CO;2, 1999.
Sud, Y. C., Lee, D., Oreopoulos, L., Barahona, D., Nenes, A., and Suarez, M. J.: Performance of McRAS-AC in the GEOS-5 AGCM: aerosol-cloud-microphysics, precipitation, cloud radiative effects, and circulation, Geosci. Model Dev., 6, 57–79, https://doi.org/10.5194/gmd-6-57-2013, 2013.
Tiedtke, M.: Representation of clouds in large-scale models, Monthly Weather Review, 121, 3040, https://doi.org/10.1175/1520-0493(1993)121<3040:ROCILS>2.0.CO;2, 1993.
Tompkins, A.: A prognostic parameterization for the subgrid-scale variability of water vapor and clouds in large-scale models and its use to diagnose cloud cover, J. Atmos. Sci., 59, 1917–1942, 2002.
Tonttila, J., O'Connor, E. J., Niemelä, S., Räisänen, P., and Järvinen, H.: Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations, Atmos. Chem. Phys., 11, 9207–9218, https://doi.org/10.5194/acp-11-9207-2011, 2011.
Twomey, S.: The influence of pollution on the shortwave cloud albedo of clouds, J. Atmos. Sci., 34, 1149–1152, 1977.
Twomey, S.: Aerosols, clouds and radiation, Atmos. Environ., 25A, 2435–2442, 1991.
Wang, M. and Penner, J. E.: Cirrus clouds in a global climate model with a statistical cirrus cloud scheme, Atmos. Chem. Phys., 10, 5449–5474, https://doi.org/10.5194/acp-10-5449-2010, 2010.
Wiacek, A., Peter, T., and Lohmann, U.: The potential influence of Asian and African mineral dust on ice, mixed-phase and liquid water clouds, Atmos. Chem. Phys., 10, 8649–8667, https://doi.org/10.5194/acp-10-8649-2010, 2010.
Wise, M. E., Baustian, K. J., Koop, T., Freedman, M. A., Jensen, E. J., and Tolbert, M. A.: Depositional ice nucleation onto crystalline hydrated NaCl particles: a new mechanism for ice formation in the troposphere, Atmos. Chem. Phys., 12, 1121–1134, https://doi.org/10.5194/acp-12-1121-2012, 2012.
Xie, P. and Arkin, P.: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs, B. Am. Meteorol. Soc., 78, 2539–2558, 1997.
Young, K. C.: The Role of Contact Nucleation in Ice Phase Initiation in Clouds, J. Atmos. Sci., 31, 768–776, https://doi.org/10.1175/1520-0469(1974)031<0768:TROCNI>2.0.CO;2, 1974.
