Articles | Volume 23, issue 1
https://doi.org/10.5194/acp-23-523-2023
© Author(s) 2023. 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-23-523-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Machine learning of cloud types in satellite observations and climate models
Department of Meteorology (MISU), Stockholm University, Stockholm, Sweden
Frida A.-M. Bender
Department of Meteorology (MISU), Stockholm University, Stockholm, Sweden
Alex Schuddeboom
School of Physical and Chemical Sciences, University of Canterbury, Christchurch, Aotearoa New Zealand
Adrian J. McDonald
School of Physical and Chemical Sciences, University of Canterbury, Christchurch, Aotearoa New Zealand
Øyvind Seland
Research and Development Department, Norwegian Meteorological Institute, Oslo, Norway
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The nextGEMS project developed two Earth system models that resolve processes of the order of 10 km, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS performed simulations with coupled ocean, land, and atmosphere over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
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Aerosol–cloud interactions over the Southern Ocean are poorly understood and remain a major source of uncertainty in climate models. This study presents ship-borne measurements, collected during a 6-week voyage into the Southern Ocean in 2018, that are an important supplement to satellite-based measurements. For example, these measurements include data on low-level clouds and aerosol composition in the marine boundary layer, which can be used in climate model evaluation efforts.
Ethan R. Dale, Stefanie Kremser, Jordis S. Tradowsky, Greg E. Bodeker, Leroy J. Bird, Gustavo Olivares, Guy Coulson, Elizabeth Somervell, Woodrow Pattinson, Jonathan Barte, Jan-Niklas Schmidt, Nariefa Abrahim, Adrian J. McDonald, and Peter Kuma
Earth Syst. Sci. Data, 13, 2053–2075, https://doi.org/10.5194/essd-13-2053-2021, https://doi.org/10.5194/essd-13-2053-2021, 2021
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MAPM is a project whose goal is to develop a method to infer particulate matter (PM) emissions maps from PM concentration measurements. In support of MAPM, we conducted a winter field campaign in New Zealand. In addition to two types of instruments measuring PM, an array of other meteorological sensors were deployed, measuring temperature and wind speed as well as probing the vertical structure of the lower atmosphere. In this article, we present the measurements taken during this campaign.
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Sara M. Blichner, Theodore Khadir, Sini Talvinen, Paulo Artaxo, Liine Heikkinen, Harri Kokkola, Radovan Krejci, Muhammed Irfan, Twan van Noije, Tuukka Petäjä, Christopher Pöhlker, Øyvind Seland, Carl Svenhag, Antti Vartiainen, and Ilona Riipinen
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Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
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Alejandro Baró Pérez, Michael S. Diamond, Frida A.-M. Bender, Abhay Devasthale, Matthias Schwarz, Julien Savre, Juha Tonttila, Harri Kokkola, Hyunho Lee, David Painemal, and Annica M. L. Ekman
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We use a numerical model to study interactions between humid light-absorbing aerosol plumes, clouds, and radiation over the southeast Atlantic. We find that the warming produced by the aerosols reduces cloud cover, especially in highly polluted situations. Aerosol impacts on drizzle play a minor role. However, aerosol effects on cloud reflectivity and moisture-induced changes in cloud cover dominate the climatic response and lead to an overall cooling by the biomass burning plumes.
Yusuf A. Bhatti, Laura E. Revell, Alex J. Schuddeboom, Adrian J. McDonald, Alex T. Archibald, Jonny Williams, Abhijith U. Venugopal, Catherine Hardacre, and Erik Behrens
Atmos. Chem. Phys., 23, 15181–15196, https://doi.org/10.5194/acp-23-15181-2023, https://doi.org/10.5194/acp-23-15181-2023, 2023
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Aerosols are a large source of uncertainty over the Southern Ocean. A dominant source of sulfate aerosol in this region is dimethyl sulfide (DMS), which is poorly simulated by climate models. We show the sensitivity of simulated atmospheric DMS to the choice of oceanic DMS data set and emission scheme. We show that oceanic DMS has twice the influence on atmospheric DMS than the emission scheme. Simulating DMS more accurately in climate models will help to constrain aerosol uncertainty.
Zhangcheng Pei, Sonya L. Fiddes, W. John R. French, Simon P. Alexander, Marc D. Mallet, Peter Kuma, and Adrian McDonald
Atmos. Chem. Phys., 23, 14691–14714, https://doi.org/10.5194/acp-23-14691-2023, https://doi.org/10.5194/acp-23-14691-2023, 2023
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In this paper, we use ground-based observations to evaluate a climate model and a satellite product in simulating surface radiation and investigate how radiation biases are influenced by cloud properties over the Southern Ocean. We find that significant radiation biases exist in both the model and satellite. The cloud fraction and cloud occurrence play an important role in affecting radiation biases. We suggest further development for the model and satellite using ground-based observations.
McKenna W. Stanford, Ann M. Fridlind, Israel Silber, Andrew S. Ackerman, Greg Cesana, Johannes Mülmenstädt, Alain Protat, Simon Alexander, and Adrian McDonald
Atmos. Chem. Phys., 23, 9037–9069, https://doi.org/10.5194/acp-23-9037-2023, https://doi.org/10.5194/acp-23-9037-2023, 2023
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Clouds play an important role in the Earth’s climate system as they modulate the amount of radiation that either reaches the surface or is reflected back to space. This study demonstrates an approach to robustly evaluate surface-based observations against a large-scale model. We find that the large-scale model precipitates too infrequently relative to observations, contrary to literature documentation suggesting otherwise based on satellite measurements.
Sushant Das, Frida Bender, and Thorsten Mauritsen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1605, https://doi.org/10.5194/egusphere-2023-1605, 2023
Preprint archived
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Astrid Fremme, Paul J. Hezel, Øyvind Seland, and Harald Sodemann
Weather Clim. Dynam., 4, 449–470, https://doi.org/10.5194/wcd-4-449-2023, https://doi.org/10.5194/wcd-4-449-2023, 2023
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We study the atmospheric moisture transport into eastern China for past, present, and future climate. Hence, we use different climate and weather prediction model data with a moisture source identification method. We find that while the moisture to first order originates mostly from similar regions, smaller changes consistently point to differences in the recycling of precipitation over land between different climates. Some differences are larger between models than between different climates.
Aiden R. Jönsson and Frida A.-M. Bender
Earth Syst. Dynam., 14, 345–365, https://doi.org/10.5194/esd-14-345-2023, https://doi.org/10.5194/esd-14-345-2023, 2023
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The Earth has nearly the same mean albedo in both hemispheres, a feature not well replicated by climate models. Global warming causes changes in surface and cloud properties that affect albedo and that feed back into the warming. We show that models predict more darkening due to ice loss in the Northern than in the Southern Hemisphere in response to increasing CO2 concentrations. This is, to varying degrees, counteracted by changes in cloud cover, with implications for cloud feedback on climate.
Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
Atmos. Chem. Phys., 22, 12873–12905, https://doi.org/10.5194/acp-22-12873-2022, https://doi.org/10.5194/acp-22-12873-2022, 2022
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We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
Petri Räisänen, Joonas Merikanto, Risto Makkonen, Mikko Savolahti, Alf Kirkevåg, Maria Sand, Øyvind Seland, and Antti-Ilari Partanen
Atmos. Chem. Phys., 22, 11579–11602, https://doi.org/10.5194/acp-22-11579-2022, https://doi.org/10.5194/acp-22-11579-2022, 2022
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A climate model is used to evaluate how the radiative forcing (RF) associated with black carbon (BC) emissions depends on the latitude, longitude, and seasonality of emissions. It is found that both the direct RF (BC absorption of solar radiation in air) and snow RF (BC absorption in snow/ice) depend strongly on the emission region and season. The results suggest that, for a given mass of BC emitted, climatic impacts are likely to be largest for high-latitude emissions due to the large snow RF.
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
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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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.
Adrien Guyot, Alain Protat, Simon P. Alexander, Andrew R. Klekociuk, Peter Kuma, and Adrian McDonald
Atmos. Meas. Tech., 15, 3663–3681, https://doi.org/10.5194/amt-15-3663-2022, https://doi.org/10.5194/amt-15-3663-2022, 2022
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Ceilometers are instruments that are widely deployed as part of operational networks. They are usually not able to detect cloud phase. Here, we propose an evaluation of various methods to detect supercooled liquid water with ceilometer observations, using an extensive dataset from Davis, Antarctica. Our results highlight the possibility for ceilometers to detect supercooled liquid water in clouds.
Alex R. Aves, Laura E. Revell, Sally Gaw, Helena Ruffell, Alex Schuddeboom, Ngaire E. Wotherspoon, Michelle LaRue, and Adrian J. McDonald
The Cryosphere, 16, 2127–2145, https://doi.org/10.5194/tc-16-2127-2022, https://doi.org/10.5194/tc-16-2127-2022, 2022
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This study confirms the presence of microplastics in Antarctic snow, highlighting the extent of plastic pollution globally. Fresh snow was collected from Ross Island, Antarctica, and subsequent analysis identified an average of 29 microplastic particles per litre of melted snow. The most likely source of these airborne microplastics is local scientific research stations; however, modelling shows their origin could have been up to 6000 km away.
Ingo Bethke, Yiguo Wang, François Counillon, Noel Keenlyside, Madlen Kimmritz, Filippa Fransner, Annette Samuelsen, Helene Langehaug, Lea Svendsen, Ping-Gin Chiu, Leilane Passos, Mats Bentsen, Chuncheng Guo, Alok Gupta, Jerry Tjiputra, Alf Kirkevåg, Dirk Olivié, Øyvind Seland, Julie Solsvik Vågane, Yuanchao Fan, and Tor Eldevik
Geosci. Model Dev., 14, 7073–7116, https://doi.org/10.5194/gmd-14-7073-2021, https://doi.org/10.5194/gmd-14-7073-2021, 2021
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The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It adds data assimilation capability to the Norwegian Earth System Model version 1 (NorESM1) and has contributed output to the Decadal Climate Prediction Project (DCPP) as part of the sixth Coupled Model Intercomparison Project (CMIP6). We describe the system and evaluate its baseline, reanalysis and prediction performance.
Stefanie Kremser, Mike Harvey, Peter Kuma, Sean Hartery, Alexia Saint-Macary, John McGregor, Alex Schuddeboom, Marc von Hobe, Sinikka T. Lennartz, Alex Geddes, Richard Querel, Adrian McDonald, Maija Peltola, Karine Sellegri, Israel Silber, Cliff S. Law, Connor J. Flynn, Andrew Marriner, Thomas C. J. Hill, Paul J. DeMott, Carson C. Hume, Graeme Plank, Geoffrey Graham, and Simon Parsons
Earth Syst. Sci. Data, 13, 3115–3153, https://doi.org/10.5194/essd-13-3115-2021, https://doi.org/10.5194/essd-13-3115-2021, 2021
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Aerosol–cloud interactions over the Southern Ocean are poorly understood and remain a major source of uncertainty in climate models. This study presents ship-borne measurements, collected during a 6-week voyage into the Southern Ocean in 2018, that are an important supplement to satellite-based measurements. For example, these measurements include data on low-level clouds and aerosol composition in the marine boundary layer, which can be used in climate model evaluation efforts.
Ethan R. Dale, Stefanie Kremser, Jordis S. Tradowsky, Greg E. Bodeker, Leroy J. Bird, Gustavo Olivares, Guy Coulson, Elizabeth Somervell, Woodrow Pattinson, Jonathan Barte, Jan-Niklas Schmidt, Nariefa Abrahim, Adrian J. McDonald, and Peter Kuma
Earth Syst. Sci. Data, 13, 2053–2075, https://doi.org/10.5194/essd-13-2053-2021, https://doi.org/10.5194/essd-13-2053-2021, 2021
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MAPM is a project whose goal is to develop a method to infer particulate matter (PM) emissions maps from PM concentration measurements. In support of MAPM, we conducted a winter field campaign in New Zealand. In addition to two types of instruments measuring PM, an array of other meteorological sensors were deployed, measuring temperature and wind speed as well as probing the vertical structure of the lower atmosphere. In this article, we present the measurements taken during this campaign.
Alejandro Baró Pérez, Abhay Devasthale, Frida A.-M. Bender, and Annica M. L. Ekman
Atmos. Chem. Phys., 21, 6053–6077, https://doi.org/10.5194/acp-21-6053-2021, https://doi.org/10.5194/acp-21-6053-2021, 2021
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We study the impacts of above-cloud biomass burning plumes on radiation and clouds over the southeast Atlantic using data derived from satellite observations and data-constrained model simulations. A substantial amount of the aerosol within the plumes is not classified as smoke by the satellite. The atmosphere warms more with increasing smoke aerosol loading. No clear influence of aerosol type, loading, or moisture within the overlying aerosol plumes is detected on the cloud top cooling rates.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
Short summary
Short summary
Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Lena Frey, Frida A.-M. Bender, and Gunilla Svensson
Atmos. Chem. Phys., 21, 577–595, https://doi.org/10.5194/acp-21-577-2021, https://doi.org/10.5194/acp-21-577-2021, 2021
Short summary
Short summary
We investigate the vertical distribution of aerosol in the climate model NorESM1-M in five regions of marine stratocumulus clouds. We thereby analyze the total aerosol extinction to facilitate a comparison with satellite data. We find that the model underestimates aerosol extinction throughout the troposphere, especially elevated aerosol layers. Further, we perform sensitivity experiments to identify the processes most important for vertical aerosol distribution in our model.
Peter Kuma, Adrian J. McDonald, Olaf Morgenstern, Richard Querel, Israel Silber, and Connor J. Flynn
Geosci. Model Dev., 14, 43–72, https://doi.org/10.5194/gmd-14-43-2021, https://doi.org/10.5194/gmd-14-43-2021, 2021
Øyvind Seland, Mats Bentsen, Dirk Olivié, Thomas Toniazzo, Ada Gjermundsen, Lise Seland Graff, Jens Boldingh Debernard, Alok Kumar Gupta, Yan-Chun He, Alf Kirkevåg, Jörg Schwinger, Jerry Tjiputra, Kjetil Schanke Aas, Ingo Bethke, Yuanchao Fan, Jan Griesfeller, Alf Grini, Chuncheng Guo, Mehmet Ilicak, Inger Helene Hafsahl Karset, Oskar Landgren, Johan Liakka, Kine Onsum Moseid, Aleksi Nummelin, Clemens Spensberger, Hui Tang, Zhongshi Zhang, Christoph Heinze, Trond Iversen, and Michael Schulz
Geosci. Model Dev., 13, 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020, https://doi.org/10.5194/gmd-13-6165-2020, 2020
Short summary
Short summary
The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. The temperature and precipitation patterns has improved compared to NorESM1. The model reaches present-day warming levels to within 0.2 °C of observed temperature but with a delayed warming during the late 20th century. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period of 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.1, and 3.9 K.
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Short summary
We present a machine learning method for determining cloud types in climate model output and satellite observations based on ground observations of cloud genera. We analyse cloud type biases and changes with temperature in climate models and show that the bias is anticorrelated with climate sensitivity. Models simulating decreasing stratiform and increasing cumuliform clouds with increased CO2 concentration tend to have higher climate sensitivity than models simulating the opposite tendencies.
We present a machine learning method for determining cloud types in climate model output and...
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