Articles | Volume 20, issue 19
https://doi.org/10.5194/acp-20-11639-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-11639-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Oct 2020
Research article |
| 14 Oct 2020
| 14 Oct 2020
Modelling mixed-phase clouds with the large-eddy model UCLALES–SALSA
Finnish Meteorological Institute, Helsinki, Finland
Hannele Korhonen
Finnish Meteorological Institute, Helsinki, Finland
Juha Tonttila
Finnish Meteorological Institute, Kuopio, Finland
Sami Romakkaniemi
Finnish Meteorological Institute, Kuopio, Finland
Harri Kokkola
Finnish Meteorological Institute, Kuopio, Finland
Tomi Raatikainen
Finnish Meteorological Institute, Helsinki, Finland
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Sini Isokääntä, Paul Kim, Santtu Mikkonen, Thomas Kühn, Harri Kokkola, Taina Yli-Juuti, Liine Heikkinen, Krista Luoma, Tuukka Petäjä, Zak Kipling, Daniel Partridge, and Annele Virtanen
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Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Marje Prank, Juha Tonttila, Jaakko Ahola, Harri Kokkola, Thomas Kühn, Sami Romakkaniemi, and Tomi Raatikainen
Atmos. Chem. Phys., 22, 10971–10992, https://doi.org/10.5194/acp-22-10971-2022, https://doi.org/10.5194/acp-22-10971-2022, 2022
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Aerosols and clouds persist as the dominant sources of uncertainty in climate projections. In this modelling study, we investigate the role of marine aerosols in influencing the lifetime of low-level clouds. Our high resolution simulations show that sea spray can both extend and shorten the lifetime of the cloud layer depending on the model setup. The impact of the primary marine organics is relatively limited while secondary aerosol from monoterpenes can have larger impact.
Petri Tiitta, Ari Leskinen, Ville A. Kaikkonen, Eero O. Molkoselkä, Anssi J. Mäkynen, Jorma Joutsensaari, Silvia Calderon, Sami Romakkaniemi, and Mika Komppula
Atmos. Meas. Tech., 15, 2993–3009, https://doi.org/10.5194/amt-15-2993-2022, https://doi.org/10.5194/amt-15-2993-2022, 2022
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Jaakko Ahola, Tomi Raatikainen, Muzaffer Ege Alper, Jukka-Pekka Keskinen, Harri Kokkola, Antti Kukkurainen, Antti Lipponen, Jia Liu, Kalle Nordling, Antti-Ilari Partanen, Sami Romakkaniemi, Petri Räisänen, Juha Tonttila, and Hannele Korhonen
Atmos. Chem. Phys., 22, 4523–4537, https://doi.org/10.5194/acp-22-4523-2022, https://doi.org/10.5194/acp-22-4523-2022, 2022
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Clouds are important for the climate, and cloud droplets have a significant role in cloud properties. Cloud droplets form when air rises and cools and water vapour condenses on small particles that can be natural or of anthropogenic origin. Currently, the updraft velocity, meaning how fast the air rises, is poorly represented in global climate models. In our study, we show three methods that will improve the depiction of updraft velocity and which properties are vital to updrafts.
Tomi Raatikainen, Marje Prank, Jaakko Ahola, Harri Kokkola, Juha Tonttila, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 3763–3778, https://doi.org/10.5194/acp-22-3763-2022, https://doi.org/10.5194/acp-22-3763-2022, 2022
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Mineral dust or similar ice-nucleating particles (INPs) are needed to initiate cloud droplet freezing at temperatures common in shallow clouds. In this work we examine how INPs that are released from the sea surface impact marine clouds. Our high-resolution simulations show that turbulent updraughts carry these particles effectively up to the clouds, where they initiate cloud droplet freezing. Sea surface INP emissions become more important with decreasing background dust INP concentrations.
Jessica Slater, Hugh Coe, Gordon McFiggans, Juha Tonttila, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 2937–2953, https://doi.org/10.5194/acp-22-2937-2022, https://doi.org/10.5194/acp-22-2937-2022, 2022
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This paper shows the specific impact of black carbon (BC) on the aerosol–planetary boundary layer (PBL) feedback and its influence on a Beijing haze episode. Overall, this paper shows that strong temperature inversions prevent BC heating within the PBL from significantly increasing PBL height, while BC above the PBL suppresses PBL development significantly through the day. From this we suggest a method by which both locally and regionally emitted BC may impact urban pollution episodes.
Jutta Kesti, John Backman, Ewan J. O'Connor, Anne Hirsikko, Eija Asmi, Minna Aurela, Ulla Makkonen, Maria Filioglou, Mika Komppula, Hannele Korhonen, and Heikki Lihavainen
Atmos. Chem. Phys., 22, 481–503, https://doi.org/10.5194/acp-22-481-2022, https://doi.org/10.5194/acp-22-481-2022, 2022
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In this study we combined aerosol particle measurements at the surface with a scanning Doppler lidar providing vertical profiles of the atmosphere to study the effect of different boundary layer conditions on aerosol particle properties in the understudied Arabian Peninsula region. The instrumentation used in this study enabled us to identify periods when pollution from remote sources was mixed down to the surface and initiated new particle formation in the growing boundary layer.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
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Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Anton Laakso, Ulrike Niemeier, Daniele Visioni, Simone Tilmes, and Harri Kokkola
Atmos. Chem. Phys., 22, 93–118, https://doi.org/10.5194/acp-22-93-2022, https://doi.org/10.5194/acp-22-93-2022, 2022
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The use of different spatio-temporal sulfur injection strategies with different magnitudes to create an artificial reflective aerosol layer to cool the climate is studied using sectional and modal aerosol schemes in a climate model. There are significant differences in the results depending on the aerosol microphysical module used. Different spatio-temporal injection strategies have a significant impact on the magnitude and zonal distribution of radiative forcing and atmospheric dynamics.
Maria Sand, Bjørn H. Samset, Gunnar Myhre, Jonas Gliß, Susanne E. Bauer, Huisheng Bian, Mian Chin, Ramiro Checa-Garcia, Paul Ginoux, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Philippe Le Sager, Marianne T. Lund, Hitoshi Matsui, Twan van Noije, Dirk J. L. Olivié, Samuel Remy, Michael Schulz, Philip Stier, Camilla W. Stjern, Toshihiko Takemura, Kostas Tsigaridis, Svetlana G. Tsyro, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, https://doi.org/10.5194/acp-21-15929-2021, 2021
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Absorption of shortwave radiation by aerosols can modify precipitation and clouds but is poorly constrained in models. A total of 15 different aerosol models from AeroCom phase III have reported total aerosol absorption, and for the first time, 11 of these models have reported in a consistent experiment the contributions to absorption from black carbon, dust, and organic aerosol. Here, we document the model diversity in aerosol absorption.
Kalle Nordling, Hannele Korhonen, Jouni Räisänen, Antti-Ilari Partanen, Bjørn H. Samset, and Joonas Merikanto
Atmos. Chem. Phys., 21, 14941–14958, https://doi.org/10.5194/acp-21-14941-2021, https://doi.org/10.5194/acp-21-14941-2021, 2021
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Understanding the temperature responses to different climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding future regional climate changes. In climate models, the regional temperature responses vary for all forcing agents, but the causes of this variability are poorly understood. For all forcing agents, the main component contributing to variance in regional surface temperature responses between the climate models is the clear-sky longwave emissivity.
Twan van Noije, Tommi Bergman, Philippe Le Sager, Declan O'Donnell, Risto Makkonen, María Gonçalves-Ageitos, Ralf Döscher, Uwe Fladrich, Jost von Hardenberg, Jukka-Pekka Keskinen, Hannele Korhonen, Anton Laakso, Stelios Myriokefalitakis, Pirkka Ollinaho, Carlos Pérez García-Pando, Thomas Reerink, Roland Schrödner, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 5637–5668, https://doi.org/10.5194/gmd-14-5637-2021, https://doi.org/10.5194/gmd-14-5637-2021, 2021
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This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in CMIP6. We give an overview of the model and describe in detail how it differs from its predecessor and the other EC-Earth3 configurations. The model's performance is characterized using coupled simulations conducted for CMIP6. The model has an effective equilibrium climate sensitivity of 3.9 °C and a transient climate response of 2.1 °C.
Joonas Merikanto, Kalle Nordling, Petri Räisänen, Jouni Räisänen, Declan O'Donnell, Antti-Ilari Partanen, and Hannele Korhonen
Atmos. Chem. Phys., 21, 5865–5881, https://doi.org/10.5194/acp-21-5865-2021, https://doi.org/10.5194/acp-21-5865-2021, 2021
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Human-induced aerosols concentrate around their emission sources, yet their climate effects span far and wide. Here, we use two climate models to robustly identify the mechanisms of how Asian anthropogenic aerosols impact temperatures across the globe. A total removal of Asian anthropogenic aerosols increases the global temperatures by 0.26 ± 0.04 °C in the models, with the strongest warming taking place over the Arctic due to increased atmospheric transport of energy towards the high north.
Antti Ruuskanen, Sami Romakkaniemi, Harri Kokkola, Antti Arola, Santtu Mikkonen, Harri Portin, Annele Virtanen, Kari E. J. Lehtinen, Mika Komppula, and Ari Leskinen
Atmos. Chem. Phys., 21, 1683–1695, https://doi.org/10.5194/acp-21-1683-2021, https://doi.org/10.5194/acp-21-1683-2021, 2021
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The study focuses mainly on cloud-scavenging efficiency of absorbing particulate matter (mainly black carbon) but additionally covers cloud-scavenging efficiency of scattering particles and statistics of cloud condensation nuclei. The main findings give insight into how black carbon is distributed in different particle sizes and the sensitivity to cloud scavenged. The main findings are useful for large-scale modelling for evaluating cloud scavenging.
Juha Tonttila, Ali Afzalifar, Harri Kokkola, Tomi Raatikainen, Hannele Korhonen, and Sami Romakkaniemi
Atmos. Chem. Phys., 21, 1035–1048, https://doi.org/10.5194/acp-21-1035-2021, https://doi.org/10.5194/acp-21-1035-2021, 2021
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The focus of this study is on rain enhancement by deliberate injection of small particles into clouds (
cloud seeding). The particles, usually released from an aircraft, are expected to enhance cloud droplet growth, but its practical feasibility is somewhat uncertain. To improve upon this, we simulate the seeding effects with a numerical model. The model reproduces the main features seen in field observations, with a strong sensitivity to the total mass of the injected particle material.
Jonas Gliß, Augustin Mortier, Michael Schulz, Elisabeth Andrews, Yves Balkanski, Susanne E. Bauer, Anna M. K. Benedictow, Huisheng Bian, Ramiro Checa-Garcia, Mian Chin, Paul Ginoux, Jan J. Griesfeller, Andreas Heckel, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Paolo Laj, Philippe Le Sager, Marianne Tronstad Lund, Cathrine Lund Myhre, Hitoshi Matsui, Gunnar Myhre, David Neubauer, Twan van Noije, Peter North, Dirk J. L. Olivié, Samuel Rémy, Larisa Sogacheva, Toshihiko Takemura, Kostas Tsigaridis, and Svetlana G. Tsyro
Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, https://doi.org/10.5194/acp-21-87-2021, 2021
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Simulated aerosol optical properties as well as the aerosol life cycle are investigated for 14 global models participating in the AeroCom initiative. Considerable diversity is found in the simulated aerosol species emissions and lifetimes, also resulting in a large diversity in the simulated aerosol mass, composition, and optical properties. A comparison with observations suggests that, on average, current models underestimate the direct effect of aerosol on the atmosphere radiation budget.
Xiaoxia Shang, Elina Giannakaki, Stephanie Bohlmann, Maria Filioglou, Annika Saarto, Antti Ruuskanen, Ari Leskinen, Sami Romakkaniemi, and Mika Komppula
Atmos. Chem. Phys., 20, 15323–15339, https://doi.org/10.5194/acp-20-15323-2020, https://doi.org/10.5194/acp-20-15323-2020, 2020
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Measurements of the multi-wavelength Raman polarization lidar PollyXT have been combined with measurements of pollen type and concentration using a traditional pollen sampler at a rural forest site in Kuopio, Finland. The depolarization ratio was enhanced when there were pollen grains in the atmosphere, illustrating the potential of lidar to track pollen grains in the atmosphere. The depolarization ratio of pure pollen particles was assessed for birch and pine pollen using a novel algorithm.
Eemeli Holopainen, Harri Kokkola, Anton Laakso, and Thomas Kühn
Geosci. Model Dev., 13, 6215–6235, https://doi.org/10.5194/gmd-13-6215-2020, https://doi.org/10.5194/gmd-13-6215-2020, 2020
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This paper introduces an in-cloud wet deposition scheme for liquid and ice phase clouds for global aerosol–climate models. With the default setup, our wet deposition scheme behaves spuriously and better representation can be achieved with this scheme when black carbon is mixed with soluble compounds at emission time. This work is done as many of the global models fail to reproduce the transport of black carbon to the Arctic, which may be due to the poor representation of wet removal in models.
Jessica Slater, Juha Tonttila, Gordon McFiggans, Paul Connolly, Sami Romakkaniemi, Thomas Kühn, and Hugh Coe
Atmos. Chem. Phys., 20, 11893–11906, https://doi.org/10.5194/acp-20-11893-2020, https://doi.org/10.5194/acp-20-11893-2020, 2020
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The feedback effect between aerosol particles, radiation and meteorology reduces turbulent motion and results in increased surface aerosol concentrations during Beijing haze. Observational analysis and regional modelling studies have examined the feedback effect but these studies are limited. In this work, we set up a high-resolution model for the Beijing environment to examine the sensitivity of the aerosol feedback effect to initial meteorological conditions and aerosol loading.
Konstantinos-Matthaios Doulgeris, Mika Komppula, Sami Romakkaniemi, Antti-Pekka Hyvärinen, Veli-Matti Kerminen, and David Brus
Atmos. Meas. Tech., 13, 5129–5147, https://doi.org/10.5194/amt-13-5129-2020, https://doi.org/10.5194/amt-13-5129-2020, 2020
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We intercompared three cloud spectrometers ground setups in conditions with frequently occurring supercooled clouds. The measurements were conducted during the Pallas Cloud Experiment (PaCE) in 2013, in the Finnish sub-Arctic region at Sammaltunturi station. The main meteorological parameters influencing the spectrometers' performance was the wind direction. Final recommendations and our view on the main limitations of each spectrometer ground setup are presented.
Innocent Kudzotsa, Harri Kokkola, Juha Tonttila, Tomi Raatikainen, and Sami Romakkaniemi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-851, https://doi.org/10.5194/acp-2020-851, 2020
Publication in ACP not foreseen
María A. Burgos, Elisabeth Andrews, Gloria Titos, Angela Benedetti, Huisheng Bian, Virginie Buchard, Gabriele Curci, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Anton Laakso, Julie Letertre-Danczak, Marianne T. Lund, Hitoshi Matsui, Gunnar Myhre, Cynthia Randles, Michael Schulz, Twan van Noije, Kai Zhang, Lucas Alados-Arboledas, Urs Baltensperger, Anne Jefferson, James Sherman, Junying Sun, Ernest Weingartner, and Paul Zieger
Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, https://doi.org/10.5194/acp-20-10231-2020, 2020
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We investigate how well models represent the enhancement in scattering coefficients due to particle water uptake, and perform an evaluation of several implementation schemes used in ten Earth system models. Our results show the importance of the parameterization of hygroscopicity and model chemistry as drivers of some of the observed diversity amongst model estimates. The definition of dry conditions and the phenomena taking place in this relative humidity range also impact the model evaluation.
Cited articles
Ahola, J.: Plotting of ice cloud simulations for research article:
“Modelling mixed-phase clouds with large-eddy model
UCLALES-SALSA”, GitHub, under release tag v1.1.4, available at: https://github.com/JaakkoAhola/LES-ice-03plotting, last
access: 10 August 2020. a
Ahola, J., Korhonen, H., Tonttila, J., Romakkaniemi, S.,
Kokkola, H., and Raatikainen, T.: UCLALES-SALSA Ice
microphysics V1.0, GitHub, under release tag IceV1.0, available at: http://github.com/UCLALES-SALSA/UCLALES-SALSA,
last access: 12 September 2019. a
Ahola, J., Korhonen, H., Tonttila, J., Romakkaniemi, S., Kokkola, H., and Raatikainen, T.: Data for research article “Modelling mixed-phase clouds with large-eddy model UCLALES-SALSA”, GitHub, available at: http://urn.fi/urn:nbn:fi:att:5144df1e-4cdf-4d5a-af46-a545ebaa4460, last access: 6 July 2020. a
Atkinson, J. D., Murray, B. J., Woodhouse, M. T., Whale, T. F., Baustian, K. J., Carslaw, K. S., Dobbie, S., O'Sullivan, D., and Malkin, T. L.: The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds, Nature, 498, 355–358, https://doi.org/10.1038/nature12278, 2013. a
Avramov, A. and Harrington, J. Y.: Influence of parameterized ice habit on simulated mixed phase Arctic clouds, J. Geophys. Res., 115, D03205, https://doi.org/10.1029/2009JD012108, 2010. a
Cox, S. K.: Cirrus Clouds and the Climate, J. Atmos. Sci., 28, 1513–1515, https://doi.org/10.1175/1520-0469(1971)028<1513:CCATC>2.0.CO;2, 1971. a
Curry, J. A.: Interactions among aerosols, clouds, and climate of the Arctic Ocean, Sci. Total Environ., 160–161, 777–791, https://doi.org/10.1016/0048-9697(95)04411-S, 1995. a
Curry, J. A., Pinto, J. O., Benner, T., and Tschudi, M.: Evolution of the cloudy boundary layer during the autumnal freezing of the Beaufort Sea, J. Geophys. Res., 102, 13851–13860, https://doi.org/10.1029/96JD03089, 1997. a
de Boer, G., Eloranta, E. W., and Shupe, M. D.: Arctic Mixed-Phase Stratiform Cloud Properties from Multiple Years of Surface-Based Measurements at Two High-Latitude Locations, J. Atmos. Sci., 66, 2874–2887, https://doi.org/10.1175/2009JAS3029.1, 2009. a
DeMott, P. J., Möhler, O., Stetzer, O., Vali, G., Levin, Z., Petters, M. D., Murakami, M., Leisner, T., Bundke, U., Klein, H., Kanji, Z. A., Cotton, R., Jones, H., Benz, S., Brinkmann, M., Rzesanke, D., Saathoff, H., Nicolet, M., Saito, A., Nillius, B., Bingemer, H., Abbatt, J., Ardon, K., Ganor, E., Georgakopoulos, D. G., and Saunders, C.: Resurgence in Ice Nuclei Measurement Research, B. Am. Meteorol. Soc., 92, 1623–1635, https://doi.org/10.1175/2011BAMS3119.1, 2011. a
Earle, M. E., Liu, P. S. K., Strapp, J. W., Zelenyuk, A., Imre, D., McFarquhar,
G. M., Shantz, N. C., and Leaitch, W. R.: Factors influencing the
microphysics and radiative properties of liquid-dominated Arctic clouds:
Insight from observations of aerosol and clouds during ISDAC, J.
Geophys. Res.-Atmos., 116, D00T09, https://doi.org/10.1029/2011JD015887, 2011. a
Filioglou, M., Mielonen, T., Balis, D., Giannakaki, E., Arola, A., Kokkola, H.,Komppula, M., and Romakkaniemi, S.: Aerosol Effect on the Cloud Phase of
Low‐Level Clouds Over the Arctic, J. Geophys. Res.-Atmos., 124, 7886–7899, https://doi.org/10.1029/2018JD030088, 2019. a, b, c
Fletcher, N. H.: The physics of rainclouds, Cambridge University Press, Pp. x, 386; 99 Figures; 6 Plates. 65s, Q. J. Roy. Meteor. Soc., 88, 559–559, https://doi.org/10.1002/qj.49708837821, 1962. a, b
Fridlind, A. M., van Diedenhoven, B., Ackerman, A. S., Avramov, A., Mrowiec, A., Morrison, H., Zuidema, P., and Shupe, M. D.: A FIRE-ACE/SHEBA Case Study of Mixed-Phase Arctic Boundary Layer Clouds: Entrainment Rate Limitations on Rapid Primary Ice Nucleation Processes, J. Atmos. Sci., 69, 365–389, https://doi.org/10.1175/JAS-D-11-052.1, 2012. a, b, c, d
Fu, Q. and Liou, K. N.: Parameterization of the Radiative Properties of Cirrus Clouds, J. Atmos. Sci., 50, 2008–2025, https://doi.org/10.1175/1520-0469(1993)050<2008:POTRPO>2.0.CO;2, 1993. a
Fu, S. and Xue, H.: The Effect of Ice Nuclei Efficiency on Arctic Mixed-Phase Clouds from Large-Eddy Simulations, J. Atmos. Sci., 74, 3901–3913, https://doi.org/10.1175/JAS-D-17-0112.1, 2017. a, b, c
Harrington, J. Y., Reisin, T., Cotton, W. R., and Kreidenweis, S. M.: Cloud resolving simulations of Arctic stratus: Part II: Transition-season clouds, Atmos. Res., 51, 45–75, https://doi.org/10.1016/S0169-8095(98)00098-2, 1999. a
Hobbs, P. V. and Rangno, A. L.: Microstructures of low and middle-level clouds over the Beaufort Sea, Q. J. Roy. Meteorol. Soc., 124, 2035–2071, https://doi.org/10.1002/qj.49712455012, 1998. a
Hoose, C., Kristjánsson, J. E., Chen, J.-P., and Hazra, A.: A Classical-Theory-Based Parameterization of Heterogeneous Ice Nucleation by Mineral Dust, Soot, and Biological Particles in a Global Climate Model, J. Atmos. Sci., 67, 2483–2503, https://doi.org/10.1175/2010JAS3425.1, 2010. a, b, c, d
Jacobson, M. Z.: Fundamentals of Atmospheric Modeling, 2nd edn., Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9781139165389, 2005. a
Jeffery, C. A. and Austin, P. H.: Homogeneous nucleation of supercooled water: Results from a new equation of state, J. Geophys. Res., 102, 25269–25279, https://doi.org/10.1029/97JD02243, 1997. a, b
Jiang, H., Cotton, W. R., Pinto, J. O., Curry, J. A., and Weissbluth, M. J.: Cloud Resolving Simulations of Mixed-Phase Arctic Stratus Observed during BASE: Sensitivity to Concentration of Ice Crystals and Large-Scale Heat and Moisture Advection, J. Atmos. Sci., 57, 2105–2117, https://doi.org/10.1175/1520-0469(2000)057<2105:CRSOMP>2.0.CO;2, 2000. a
Khain, A., Pokrovsky, A., Pinsky, M., Seifert, A., and Phillips, V.: Simulation of Effects of Atmospheric Aerosols on Deep Turbulent Convective Clouds Using a Spectral Microphysics Mixed-Phase Cumulus Cloud Model. Part I: Model Description and Possible Applications, J. Atmos. Sci., 61, 2963–2982, https://doi.org/10.1175/JAS-3350.1, 2004. a, b
Khvorostyanov, V. I. and Curry, J. A.: The Theory of Ice Nucleation by Heterogeneous Freezing of Deliquescent Mixed CCN. Part I: Critical Radius, Energy, and Nucleation Rate, J. Atmos. Sci., 61, 2676–2691, https://doi.org/10.1175/JAS3266.1, 2004. a, b, c
Kiselev, A., Bachmann, F., Pedevilla, P., Cox, S. J., Michaelides, A., Gerthsen, D., and Leisner, T.: Active sites in heterogeneous ice nucleation–the example of K-rich feldspars, Science, 355, 367–371, https://doi.org/10.1126/science.aai8034, 2017. a
Klein, S. A., McCoy, R. B., Morrison, H., Ackerman, A. S., Avramov, A., de Boer, G., Chen, M., Cole, J. N. S., Del Genio, A. D., Falk, M., Foster, M. J., Fridlind, A., Golaz, J.-C., Hashino, T., Harrington, J. Y., Hoose, C., Khairoutdinov, M. F., Larson, V. E., Liu, X., Luo, Y., McFarquhar, G. M., Menon, S., Neggers, R. A. J., Park, S., Poellot, M. R., Schmidt, J. M., Sednev, I., Shipway, B. J., Shupe, M. D., Spangenberg, D. A., Sud, Y. C., Turner, D. D., Veron, D. E., von Salzen, K., Walker, G. K., Wang, Z., Wolf, A. B., Xie, S., Xu, X.-M., Yang, F., and Zhang, G.: Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single-layer cloud, Q. J. Roy. Meteor. Soc., 135, 979–1002, https://doi.org/10.1002/qj.416, 2009. a, b
Knight, N. C. and Heymsfield, A. J.: Measurement and Interpretation of Hailstone Density and Terminal Velocity, J. Atmos. Sci., 40, 1510–1516, https://doi.org/10.1175/1520-0469(1983)040<1510:MAIOHD>2.0.CO;2, 1983. a
Kokkola, H., Korhonen, H., Lehtinen, K. E. J., Makkonen, R., Asmi, A., Järvenoja, S., Anttila, T., Partanen, A.-I., Kulmala, M., Järvinen, H., Laaksonen, A., and Kerminen, V.-M.: SALSA – a Sectional Aerosol module for Large Scale Applications, Atmos. Chem. Phys., 8, 2469–2483, https://doi.org/10.5194/acp-8-2469-2008, 2008. a
Kokkola, H., Kühn, T., Laakso, A., Bergman, T., Lehtinen, K. E. J., Mielonen, T., Arola, A., Stadtler, S., Korhonen, H., Ferrachat, S., Lohmann, U., Neubauer, D., Tegen, I., Siegenthaler-Le Drian, C., Schultz, M. G., Bey, I., Stier, P., Daskalakis, N., Heald, C. L., and Romakkaniemi, S.: SALSA2.0: The sectional aerosol module of the aerosol–chemistry–climate model ECHAM6.3.0-HAM2.3-MOZ1.0, Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, 2018. a
Lebo, Z. J., Johnson, N. C., and Harrington, J. Y.: Radiative influences on ice crystal and droplet growth within mixed-phase stratus clouds, J. Geophys. Res., 113, D09203, https://doi.org/10.1029/2007JD009262, 2008. a
Li, Z., Xue, H., and Yang, F.: A modeling study of ice formation affected by aerosols, J. Geophys. Res.-Atmos., 118, 11213–11227, https://doi.org/10.1002/jgrd.50861, 2013. a, b
McFarquhar, G. M., Ghan, S., Verlinde, J., Korolev, A., Strapp, J. W., Schmid, B., Tomlinson, J. M., Wolde, M., Brooks, S. D., Cziczo, D., Dubey, M. K., Fan, J., Flynn, C., Gultepe, I., Hubbe, J., Gilles, M. K., Laskin, A., Lawson, P., Leaitch, W. R., Liu, P., Liu, X., Lubin, D., Mazzoleni, C., Macdonald, A.-M., Moffet, R. C., Morrison, H., Ovchinnikov, M., Shupe, M. D., Turner, D. D., Xie, S., Zelenyuk, A., Bae, K., Freer, M., and Glen, A.: Indirect and Semi-direct Aerosol Campaign, B. Am. Meteorol. Soc., 92, 183–201, https://doi.org/10.1175/2010BAMS2935.1, 2011. a, b, c
Morrison, H.: On the robustness of aerosol effects on an idealized supercell storm simulated with a cloud system-resolving model, Atmos. Chem. Phys., 12, 7689–7705, https://doi.org/10.5194/acp-12-7689-2012, 2012. a
Morrison, H., Shupe, M. D., Pinto, J. O., and Curry, J. A.: Possible roles of ice nucleation mode and ice nuclei depletion in the extended lifetime of Arctic mixed‐phase clouds, Geophys. Res. Lett., 32, L18801, https://doi.org/10.1029/2005GL023614, 2005. a
Morrison, H., Zuidema, P., Ackerman, A. S., Avramov, A., de Boer, G., Fan, J., Fridlind, A. M., Hashino, T., Harrington, J. Y., Luo, Y., Ovchinnikov, M., and Shipway, B.: Intercomparison of cloud model simulations of Arctic mixed-phase boundary layer clouds observed during SHEBA/FIRE-ACE, J. Adv. Model. Earth Sy., 3, M06003, https://doi.org/10.1029/2011MS000066, 2011b. a, b, c
Norgren, M. S., de Boer, G., and Shupe, M. D.: Observed aerosol suppression of cloud ice in low-level Arctic mixed-phase clouds, Atmos. Chem. Phys., 18, 13345–13361, https://doi.org/10.5194/acp-18-13345-2018, 2018. a
Ovchinnikov, M., Ackerman, A. S., Avramov, A., Cheng, A., Fan, J., Fridlind, A. M., Ghan, S., Harrington, J., Hoose, C., Korolev, A., McFarquhar, G. M., Morrison, H., Paukert, M., Savre, J., Shipway, B. J., Shupe, M. D., Solomon, A., and Sulia, K.: Intercomparison of large-eddy simulations of Arctic mixed-phase clouds: Importance of ice size distribution assumptions, J. Adv. Model. Earth Sy., 6, 223–248, https://doi.org/10.1002/2013MS000282, 2014. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v
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. a
Petters, M. D., Prenni, A. J., Kreidenweis, S. M., DeMott, P. J., Matsunaga, A., Lim, Y. B., and Ziemann, P. J.: Chemical aging and the hydrophobic-to-hydrophilic conversion of carbonaceous aerosol, Geophys. Res.
Lett., 33, L24806, https://doi.org/10.1029/2006GL027249, 2006. a
Phillips, V. T. J., DeMott, P. J., 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. a
Pinto, J. O.: Autumnal Mixed-Phase Cloudy Boundary Layers in the Arctic, J. Atmos. Sci., 55, 2016–2038, https://doi.org/10.1175/1520-0469(1998)055<2016:AMPCBL>2.0.CO;2, 1998. a
Rangno, A. L. and Hobbs, P. V.: Ice particles in stratiform clouds in the Arctic and possible mechanisms for the production of high ice concentrations, J. Geophys. Res., 106, 15065–15075, https://doi.org/10.1029/2000JD900286, 2001. a
Rauber, R. M. and Tokay, A.: An Explanation for the Existence of Supercooled Water at the Top of Cold Clouds, J. Atmos. Sci., 48, 1005–1023, https://doi.org/10.1175/1520-0469(1991)048<1005:AEFTEO>2.0.CO;2, 1991. a
Savre, J. and Ekman, A. M. L.: Large‐eddy simulation of three mixed‐phase cloud events during ISDAC: Conditions for persistent heterogeneous ice formation, J. Geophys. Res.-Atmos., 120, 7699–7725, https://doi.org/10.1002/2014JD023006, 2015. a, b, c, d
Shupe, M. D., Matrosov, S. Y., and Uttal, T.: Arctic Mixed-Phase Cloud Properties Derived from Surface-Based Sensors at SHEBA, J. Atmos. Sci., 63, 697–711, https://doi.org/10.1175/JAS3659.1, 2006. a
Solomon, A., Feingold, G., and Shupe, M. D.: The role of ice nuclei recycling in the maintenance of cloud ice in Arctic mixed-phase stratocumulus, Atmos. Chem. Phys., 15, 10631–10643, https://doi.org/10.5194/acp-15-10631-2015, 2015. a, b, c
Solomon, A., de Boer, G., Creamean, J. M., McComiskey, A., Shupe, M. D., Maahn, M., and Cox, C.: The relative impact of cloud condensation nuclei and ice nucleating particle concentrations on phase partitioning in Arctic mixed-phase stratocumulus clouds, Atmos. Chem. Phys., 18, 17047–17059, https://doi.org/10.5194/acp-18-17047-2018, 2018.
a, b
Solomon, S., Qin, D., Manning, M., Marquis, M., Averyt, K., Tignor, M. M. B., Miller, H. L., and Chen, Z.: Climate Change 2007: The Physical Science Basis, Cambridge University Press, UK, and New York, NY, USA, 2007. a
Stevens, B. and Feingold, G.: Untangling aerosol effects on clouds and precipitation in a buffered system, Nature, 461, 607–613, https://doi.org/10.1038/nature08281, 2009. a
Stevens, B., Moeng, C.-H., and Sullivan, P. P.: Large-Eddy Simulations of Radiatively Driven Convection: Sensitivities to the Representation of Small Scales, J. Atmos. Sci., 56, 3963–3984, https://doi.org/10.1175/1520-0469(1999)056<3963:LESORD>2.0.CO;2, 1999. a
Stevens, B., Moeng, C.-H., Ackerman, A. S., Bretherton, C. S., Chlond, A., de Roode, S., Edwards, J., Golaz, J.-C., Jiang, H., Khairoutdinov, M., Kirkpatrick, M. P., Lewellen, D. C., Lock, A., Müller, F., Stevens, D. E., Whelan, E., and Zhu, P.: Evaluation of Large-Eddy Simulations via Observations of Nocturnal Marine Stratocumulus, Mon. Weather Rev., 133, 1443–1462, https://doi.org/10.1175/MWR2930.1, 2005. a
Stevens, R. G., Loewe, K., Dearden, C., Dimitrelos, A., Possner, A., Eirund, G. K., Raatikainen, T., Hill, A. A., Shipway, B. J., Wilkinson, J., Romakkaniemi, S., Tonttila, J., Laaksonen, A., Korhonen, H., Connolly, P., Lohmann, U., Hoose, C., Ekman, A. M. L., Carslaw, K. S., and Field, P. R.: A model intercomparison of CCN-limited tenuous clouds in the high Arctic, Atmos. Chem. Phys., 18, 11041–11071, https://doi.org/10.5194/acp-18-11041-2018, 2018. a
Stokes, R. H. and Robinson, R. A.: Interactions in Aqueous Nonelectrolyte Solutions. I. Solute-Solvent Equilibria, J. Chem. Phys., 70, 2126–2131, https://doi.org/10.1021/j100879a010, 1966. a
Tonttila, J., Maalick, Z., Raatikainen, T., Kokkola, H., Kühn, T., and Romakkaniemi, S.: UCLALES–SALSA v1.0: a large-eddy model with interactive sectional microphysics for aerosol, clouds and precipitation, Geosci. Model Dev., 10, 169–188, https://doi.org/10.5194/gmd-10-169-2017, 2017. a, b, c, d, e, f, g, h, i, j, k
Verlinde, J., Harrington, J. Y., McFarquhar, G. M., Yannuzzi, V. T., Avramov, A., Greenberg, S., Johnson, N., Zhang, G., Poellot, M. R., Mather, J. H., Turner, D. D., Eloranta, E. W., Zak, B. D., Prenni, A. J., Daniel, J. S., Kok, G. L., Tobin, D. C., Holz, R., Sassen, K., Spangenberg, D., Minnis, P., Tooman, T. P., Ivey, M. D., Richardson, S. J., Bahrmann, C. P., Shupe, M., DeMott, P. J., Heymsfield, A. J., and Schofield, R.: The Mixed-Phase Arctic Cloud Experiment, B. Am. Meteorol. Soc., 88, 205–222, https://doi.org/10.1175/BAMS-88-2-205, 2007. a
Zdanovskii, A. B.: Trudy Solyanoi Laboratorii, Akad. Nauk SSSR, No. 2, 1936. a
Zuidema, P., Baker, B., Han, Y., Intrieri, J., Key, J., Lawson, P., Matrosov, S., Shupe, M., Stone, R., and Uttal, T.: An Arctic Springtime Mixed-Phase Cloudy Boundary Layer Observed during SHEBA, J. Atmos. Sci., 62, 160–176, https://doi.org/10.1175/JAS-3368.1, 2005. a
Short summary
In this study, we present an improved cloud model that reproduces the behaviour of mixed-phase clouds containing liquid droplets and ice crystals in more detail than before. This model is a convenient computational tool that enables the study of phenomena that cannot fit into a laboratory. These clouds have a significant role in climate, but they are not yet properly understood. Here, we show the advantages of the new model in a case study focusing on Arctic mixed-phase clouds.
In this study, we present an improved cloud model that reproduces the behaviour of mixed-phase...
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