Articles | Volume 23, issue 20
https://doi.org/10.5194/acp-23-13125-2023
© 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-23-13125-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
18 Oct 2023
Research article | Highlight paper |
| 18 Oct 2023
| 18 Oct 2023
Global observations of aerosol indirect effects from marine liquid clouds
Department of Geosciences, University of Oslo, Oslo, 0371, Norway
Trude Storelvmo
Department of Geosciences, University of Oslo, Oslo, 0371, Norway
Graduate School of Business, Nord University, Bodø, 8026, Norway
Anna Possner
Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt, Germany
Related authors
Brandon M. Duran, Casey J. Wall, Nicholas J. Lutsko, Takuro Michibata, Po-Lun Ma, Yi Qin, Margaret L. Duffy, Brian Medeiros, and Matvey Debolskiy
EGUsphere, https://doi.org/10.5194/egusphere-2024-3063, https://doi.org/10.5194/egusphere-2024-3063, 2024
Short summary
Short summary
We use satellite simulator data generated by global climate models to investigate how aerosol particles impact the radiative properties of liquid clouds. Specifically, we quantify the radiative perturbations arising from aerosol-driven changes in the number density of cloud droplets, the vertically integrated cloud water mass, and the cloud amount. Our results show that in models, aerosol effects on the number density of cloud droplets contributes the most to anthropogenic climate forcing.
Hendrik Andersen, Jan Cermak, Alyson Douglas, Timothy A. Myers, Peer Nowack, Philip Stier, Casey J. Wall, and Sarah Wilson Kemsley
Atmos. Chem. Phys., 23, 10775–10794, https://doi.org/10.5194/acp-23-10775-2023, https://doi.org/10.5194/acp-23-10775-2023, 2023
Short summary
Short summary
This study uses an observation-based cloud-controlling factor framework to study near-global sensitivities of cloud radiative effects to a large number of meteorological and aerosol controls. We present near-global sensitivity patterns to selected thermodynamic, dynamic, and aerosol factors and discuss the physical mechanisms underlying the derived sensitivities. Our study hopes to guide future analyses aimed at constraining cloud feedbacks and aerosol–cloud interactions.
Robert Pincus, Paul A. Hubanks, Steven Platnick, Kerry Meyer, Robert E. Holz, Denis Botambekov, and Casey J. Wall
Earth Syst. Sci. Data, 15, 2483–2497, https://doi.org/10.5194/essd-15-2483-2023, https://doi.org/10.5194/essd-15-2483-2023, 2023
Short summary
Short summary
This paper describes a new global dataset of cloud properties observed by a specific satellite program created to facilitate comparison with a matching observational proxy used in climate models. Statistics are accumulated over daily and monthly timescales on an equal-angle grid. Statistics include cloud detection, cloud-top pressure, and cloud optical properties. Joint histograms of several variable pairs are also available.
Florian Sauerland, Niels Souverijns, Anna Possner, Heike Wex, Preben Van Overmeiren, Alexander Mangold, Kwinten Van Weverberg, and Nicole van Lipzig
Atmos. Chem. Phys., 24, 13751–13768, https://doi.org/10.5194/acp-24-13751-2024, https://doi.org/10.5194/acp-24-13751-2024, 2024
Short summary
Short summary
We use a regional climate model, COSMO-CLM², enhanced with a module resolving aerosol processes, to study Antarctic clouds. We prescribe different concentrations of ice-nucleating particles to our model to assess how these clouds respond to concentration changes, validating results with cloud and aerosol observations from the Princess Elisabeth Antarctica station. Our results show that aerosol–cloud interactions vary with temperature, providing valuable insights into Antarctic cloud dynamics.
Ragnhild Bieltvedt Skeie, Magne Aldrin, Terje K. Berntsen, Marit Holden, Ragnar Bang Huseby, Gunnar Myhre, and Trude Storelvmo
Earth Syst. Dynam., 15, 1435–1458, https://doi.org/10.5194/esd-15-1435-2024, https://doi.org/10.5194/esd-15-1435-2024, 2024
Short summary
Short summary
Climate sensitivity and aerosol forcing are central quantities in climate science that are uncertain and contribute to the spread in climate projections. To constrain them, we use observations of temperature and ocean heat content as well as prior knowledge of radiative forcings over the industrialized period. The estimates are sensitive to how aerosol cooling evolved over the latter part of the 20th century, and a strong aerosol forcing trend in the 1960s–1970s is not supported by our analysis.
Brandon M. Duran, Casey J. Wall, Nicholas J. Lutsko, Takuro Michibata, Po-Lun Ma, Yi Qin, Margaret L. Duffy, Brian Medeiros, and Matvey Debolskiy
EGUsphere, https://doi.org/10.5194/egusphere-2024-3063, https://doi.org/10.5194/egusphere-2024-3063, 2024
Short summary
Short summary
We use satellite simulator data generated by global climate models to investigate how aerosol particles impact the radiative properties of liquid clouds. Specifically, we quantify the radiative perturbations arising from aerosol-driven changes in the number density of cloud droplets, the vertically integrated cloud water mass, and the cloud amount. Our results show that in models, aerosol effects on the number density of cloud droplets contributes the most to anthropogenic climate forcing.
Tómas Zoëga, Trude Storelvmo, and Kirstin Krüger
EGUsphere, https://doi.org/10.5194/egusphere-2024-2651, https://doi.org/10.5194/egusphere-2024-2651, 2024
Short summary
Short summary
We use an Earth system model to systematically investigate the climate response to high-latitude, effusive volcanic eruptions as a function of eruption season and size with a special focus on the Arctic. We find that different seasons strongly modulate the climate response with Arctic surface warming in winter and cooling in summer. Also, as eruptions become larger in terms of sulfur dioxide emissions, the climate response becomes increasingly insensitive to variations in the emission strength.
Astrid Bragstad Gjelsvik, Robert Oscar David, Tim Carlsen, Franziska Hellmuth, Stefan Hofer, Zachary McGraw, Harald Sodemann, and Trude Storelvmo
EGUsphere, https://doi.org/10.5194/egusphere-2024-1879, https://doi.org/10.5194/egusphere-2024-1879, 2024
Short summary
Short summary
Ice formation in clouds has a substantial impact on radiation and precipitation, and must be realistically simulated in order to understand present and future Arctic climate. Rare aerosols known as ice-nucleating particles can play an important role for cloud ice formation, but their representation in global climate models is not well suited for the Arctic. In this study, the simulation of cloud phase is improved when the representation of these particles are constrained by Arctic observations.
Britta Schäfer, Robert Oscar David, Paraskevi Georgakaki, Julie Thérèse Pasquier, Georgia Sotiropoulou, and Trude Storelvmo
Atmos. Chem. Phys., 24, 7179–7202, https://doi.org/10.5194/acp-24-7179-2024, https://doi.org/10.5194/acp-24-7179-2024, 2024
Short summary
Short summary
Mixed-phase clouds, i.e., clouds consisting of ice and supercooled water, are very common in the Arctic. However, how these clouds form is often not correctly represented in standard weather models. We show that both ice crystal concentrations in the cloud and precipitation from the cloud can be improved in the model when aerosol concentrations are prescribed from observations and when more processes for ice multiplication, i.e., the production of new ice particles from existing ice, are added.
Franziska Hellmuth, Tim Carlsen, Anne Sophie Daloz, Robert Oscar David, and Trude Storelvmo
EGUsphere, https://doi.org/10.5194/egusphere-2024-754, https://doi.org/10.5194/egusphere-2024-754, 2024
Short summary
Short summary
This article compares the occurrence of supercooled liquid-containing clouds (sLCCs) and their link to surface snowfall in CloudSat-CALIPSO, ERA5, and CMIP6 models. Significant discrepancies were found, with ERA5 and CMIP6 consistently overestimating sLCC and snowfall frequency. This bias is likely due to cloud microphysics parameterization. This conclusion has implications for accurately representing cloud phase and snowfall in future climate projections.
Idunn Aamnes Mostue, Stefan Hofer, Trude Storelvmo, and Xavier Fettweis
The Cryosphere, 18, 475–488, https://doi.org/10.5194/tc-18-475-2024, https://doi.org/10.5194/tc-18-475-2024, 2024
Short summary
Short summary
The latest generation of climate models (Coupled Model Intercomparison Project Phase 6 – CMIP6) warm more over Greenland and the Arctic and thus also project a larger mass loss from the Greenland Ice Sheet (GrIS) compared to the previous generation of climate models (CMIP5). Our work suggests for the first time that part of the greater mass loss in CMIP6 over the GrIS is driven by a difference in the surface mass balance sensitivity from a change in cloud representation in the CMIP6 models.
Hendrik Andersen, Jan Cermak, Alyson Douglas, Timothy A. Myers, Peer Nowack, Philip Stier, Casey J. Wall, and Sarah Wilson Kemsley
Atmos. Chem. Phys., 23, 10775–10794, https://doi.org/10.5194/acp-23-10775-2023, https://doi.org/10.5194/acp-23-10775-2023, 2023
Short summary
Short summary
This study uses an observation-based cloud-controlling factor framework to study near-global sensitivities of cloud radiative effects to a large number of meteorological and aerosol controls. We present near-global sensitivity patterns to selected thermodynamic, dynamic, and aerosol factors and discuss the physical mechanisms underlying the derived sensitivities. Our study hopes to guide future analyses aimed at constraining cloud feedbacks and aerosol–cloud interactions.
Robert Pincus, Paul A. Hubanks, Steven Platnick, Kerry Meyer, Robert E. Holz, Denis Botambekov, and Casey J. Wall
Earth Syst. Sci. Data, 15, 2483–2497, https://doi.org/10.5194/essd-15-2483-2023, https://doi.org/10.5194/essd-15-2483-2023, 2023
Short summary
Short summary
This paper describes a new global dataset of cloud properties observed by a specific satellite program created to facilitate comparison with a matching observational proxy used in climate models. Statistics are accumulated over daily and monthly timescales on an equal-angle grid. Statistics include cloud detection, cloud-top pressure, and cloud optical properties. Joint histograms of several variable pairs are also available.
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
Geosci. Model Dev., 16, 1735–1754, https://doi.org/10.5194/gmd-16-1735-2023, https://doi.org/10.5194/gmd-16-1735-2023, 2023
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), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
Jessica Danker, Odran Sourdeval, Isabel L. McCoy, Robert Wood, and Anna Possner
Atmos. Chem. Phys., 22, 10247–10265, https://doi.org/10.5194/acp-22-10247-2022, https://doi.org/10.5194/acp-22-10247-2022, 2022
Short summary
Short summary
Using spaceborne lidar-radar retrievals, we show that seasonal changes in cloud phase outweigh changes in cloud-phase statistics across cloud morphologies at given cloud-top temperatures. These results show that cloud morphology does not seem to pose a primary constraint on cloud-phase statistics in the Southern Ocean. Meanwhile, larger changes in in-cloud albedo across cloud morphologies are observed in supercooled liquid rather than mixed-phase stratocumuli.
Britta Schäfer, Tim Carlsen, Ingrid Hanssen, Michael Gausa, and Trude Storelvmo
Atmos. Chem. Phys., 22, 9537–9551, https://doi.org/10.5194/acp-22-9537-2022, https://doi.org/10.5194/acp-22-9537-2022, 2022
Short summary
Short summary
Cloud properties are important for the surface radiation budget. This study presents cold-cloud observations based on lidar measurements from the Norwegian Arctic between 2011 and 2017. Using statistical assessments and case studies, we give an overview of the macro- and microphysical properties of these clouds and demonstrate the capabilities of long-term cloud observations in the Norwegian Arctic from the ground-based lidar at Andenes.
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.
Sorin Nicolae Vâjâiac, Andreea Calcan, Robert Oscar David, Denisa-Elena Moacă, Gabriela Iorga, Trude Storelvmo, Viorel Vulturescu, and Valeriu Filip
Atmos. Meas. Tech., 14, 6777–6794, https://doi.org/10.5194/amt-14-6777-2021, https://doi.org/10.5194/amt-14-6777-2021, 2021
Short summary
Short summary
Warm clouds (with liquid droplets) play an important role in modulating the amount of incoming solar radiation to Earth’s surface and thus the climate. The most efficient way to study them is by in situ optical measurements. This paper proposes a new methodology for providing more detailed and reliable structural analyses of warm clouds through post-flight processing of collected data. The impact fine aerosol incorporation in water droplets might have on such measurements is also discussed.
Kine Onsum Moseid, Michael Schulz, Trude Storelvmo, Ingeborg Rian Julsrud, Dirk Olivié, Pierre Nabat, Martin Wild, Jason N. S. Cole, Toshihiko Takemura, Naga Oshima, Susanne E. Bauer, and Guillaume Gastineau
Atmos. Chem. Phys., 20, 16023–16040, https://doi.org/10.5194/acp-20-16023-2020, https://doi.org/10.5194/acp-20-16023-2020, 2020
Short summary
Short summary
In this study we compare solar radiation at the surface from observations and Earth system models from 1961 to 2014. We find that the models do not reproduce the so-called
global dimmingas found in observations. Only model experiments with anthropogenic aerosol emissions display any dimming at all. The discrepancies between observations and models are largest in China, which we suggest is in part due to erroneous aerosol precursor emission inventories in the emission dataset used for CMIP6.
Anna Possner, Ryan Eastman, Frida Bender, and Franziska Glassmeier
Atmos. Chem. Phys., 20, 3609–3621, https://doi.org/10.5194/acp-20-3609-2020, https://doi.org/10.5194/acp-20-3609-2020, 2020
Short summary
Short summary
Cloud water content and the number of droplets inside clouds covary with boundary layer depth. This covariation may amplify the change in water content due to a change in droplet number inferred from long-term observations. Taking this into account shows that the change in water content for increased droplet number in observations and high-resolution simulations agrees in shallow boundary layers. Meanwhile, deep boundary layers are under-sampled in process-scale simulations and observations.
Gesa K. Eirund, Anna Possner, and Ulrike Lohmann
Atmos. Chem. Phys., 19, 9847–9864, https://doi.org/10.5194/acp-19-9847-2019, https://doi.org/10.5194/acp-19-9847-2019, 2019
Short summary
Short summary
Low-level mixed-phase cloud (MPC) properties can be highly affected by the ambient aerosol concentration, especially in pristine environments like the Arctic. By employing high-resolution model simulations we investigate the response of a MPC over an open ocean and a sea ice surface to aerosol perturbations. While we find a strong initial sensitivity to changes in aerosol concentration in both cloud regimes, the magnitude as well as the long-term cloud response depends on the surface condition.
Anna Possner, Hailong Wang, Robert Wood, Ken Caldeira, and Thomas P. Ackerman
Atmos. Chem. Phys., 18, 17475–17488, https://doi.org/10.5194/acp-18-17475-2018, https://doi.org/10.5194/acp-18-17475-2018, 2018
Short summary
Short summary
We quantify aerosol–cloud radiative interactions in a regime of deep open-cell stratocumuli (boundary layer depth 1.5 km), a regime which remains largely unexplored within this context and yet is more dominant than cases of shallow stratocumuli previously studied. We simulate substantial increases in albedo in a regime where ship tracks are not found and argue that such changes may escape detection and attribution through remote sensing due to the large natural variability in the system.
Robin G. Stevens, Katharina Loewe, Christopher Dearden, Antonios Dimitrelos, Anna Possner, Gesa K. Eirund, Tomi Raatikainen, Adrian A. Hill, Benjamin J. Shipway, Jonathan Wilkinson, Sami Romakkaniemi, Juha Tonttila, Ari Laaksonen, Hannele Korhonen, Paul Connolly, Ulrike Lohmann, Corinna Hoose, Annica M. L. Ekman, Ken S. Carslaw, and Paul R. Field
Atmos. Chem. Phys., 18, 11041–11071, https://doi.org/10.5194/acp-18-11041-2018, https://doi.org/10.5194/acp-18-11041-2018, 2018
Short summary
Short summary
We perform a model intercomparison of summertime high Arctic clouds. Observed concentrations of aerosol particles necessary for cloud formation fell to extremely low values, coincident with a transition from cloudy to nearly cloud-free conditions. Previous analyses have suggested that at these low concentrations, the radiative properties of the clouds are determined primarily by these particle concentrations. The model results strongly support this hypothesis.
Inger Helene Hafsahl Karset, Terje Koren Berntsen, Trude Storelvmo, Kari Alterskjær, Alf Grini, Dirk Olivié, Alf Kirkevåg, Øyvind Seland, Trond Iversen, and Michael Schulz
Atmos. Chem. Phys., 18, 7669–7690, https://doi.org/10.5194/acp-18-7669-2018, https://doi.org/10.5194/acp-18-7669-2018, 2018
Short summary
Short summary
This study highlights the role of oxidants in modeling of the preindustrial-to-present-day aerosol indirect effects. We argue that the aerosol precursor gases should be exposed to oxidants of its era to get a more correct representation of secondary aerosol formation. Our global model simulations show that the total aerosol indirect effect changes from −1.32 to −1.07 W m−2 when the precursor gases in the preindustrial simulation are exposed to preindustrial instead of present-day oxidants.
Yaoxian Huang, Nadine Unger, Trude Storelvmo, Kandice Harper, Yiqi Zheng, and Chris Heyes
Atmos. Chem. Phys., 18, 5219–5233, https://doi.org/10.5194/acp-18-5219-2018, https://doi.org/10.5194/acp-18-5219-2018, 2018
Short summary
Short summary
We apply a global 3-D climate model to quantify the climate impacts of carbonaceous aerosols from solid fuel cookstove emissions. Without black carbon (BC) serving as ice nuclei (IN), global and Indian solid fuel cookstove aerosol emissions have net global cooling impacts. However, when BC acts as IN, the net sign of radiative impacts of carbonaceous aerosols from solid fuel cookstove emissions varies with the choice of maximum freezing efficiency of BC during ice cloud formation.
Franziska Glassmeier, Anna Possner, Bernhard Vogel, Heike Vogel, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 8651–8680, https://doi.org/10.5194/acp-17-8651-2017, https://doi.org/10.5194/acp-17-8651-2017, 2017
Short summary
Short summary
We compare two chemistry and aerosol schemes – one designed for air-quality, the other for climate applications. For distribution, composition and radiative properties, the choice of aerosol types and processes turns out to be more important than their implementation. For aerosol–cloud interactions, we find cloud processes, in particular ice formation, to be the main obstacle to our understanding.
Jane E. Smyth, Rick D. Russotto, and Trude Storelvmo
Atmos. Chem. Phys., 17, 6439–6453, https://doi.org/10.5194/acp-17-6439-2017, https://doi.org/10.5194/acp-17-6439-2017, 2017
Short summary
Short summary
Geoengineering is a controversial proposal to counteract global warming by reducing the incoming solar radiation. Solar dimming could restore preindustrial temperatures, but global rainfall patterns would be altered. We analyze the global rainfall changes in 11 climate model simulations of solar dimming to better understand the underlying processes. We conclude that tropical precipitation would be substantially altered, in part due to changes in the large-scale atmospheric circulation.
B. Kravitz, A. Robock, S. Tilmes, O. Boucher, J. M. English, P. J. Irvine, A. Jones, M. G. Lawrence, M. MacCracken, H. Muri, J. C. Moore, U. Niemeier, S. J. Phipps, J. Sillmann, T. Storelvmo, H. Wang, and S. Watanabe
Geosci. Model Dev., 8, 3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, https://doi.org/10.5194/gmd-8-3379-2015, 2015
A. Possner, E. Zubler, U. Lohmann, and C. Schär
Atmos. Chem. Phys., 15, 2185–2201, https://doi.org/10.5194/acp-15-2185-2015, https://doi.org/10.5194/acp-15-2185-2015, 2015
Short summary
Short summary
For the first time, real-case simulations of ship tracks are performed at the 2km scale and evaluated against observations. Simulations show that ship tracks are quantitatively and qualitatively captured by the model. Therefore, this approach could be used to evaluate the interplay between parameterisations for aerosol–cloud interactions which occur, in the case of ship tracks, in spatially defined regions and under constrained environmental conditions.
A. Takeishi and T. Storelvmo
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-24087-2014, https://doi.org/10.5194/acpd-14-24087-2014, 2014
Revised manuscript not accepted
Related subject area
Subject: Climate and Earth System | Research Activity: Remote Sensing | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Evaluation of total column water vapour products from satellite observations and reanalyses within the GEWEX Water Vapor Assessment
Relations between cyclones and ozone changes in the Arctic using data from satellite instruments and the MOSAiC ship campaign
Tim Trent, Marc Schröder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinski, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
Atmos. Chem. Phys., 24, 9667–9695, https://doi.org/10.5194/acp-24-9667-2024, https://doi.org/10.5194/acp-24-9667-2024, 2024
Short summary
Short summary
In a warmer future, water vapour will spend more time in the atmosphere, changing global rainfall patterns. In this study, we analysed the performance of 28 water vapour records between 1988 and 2014. We find sensitivity to surface warming generally outside expected ranges, attributed to breakpoints in individual record trends and differing representations of climate variability. The implication is that longer records are required for high confidence in assessing climate trends.
Falco Monsees, Alexei Rozanov, John P. Burrows, Mark Weber, Annette Rinke, Ralf Jaiser, and Peter von der Gathen
Atmos. Chem. Phys., 24, 9085–9099, https://doi.org/10.5194/acp-24-9085-2024, https://doi.org/10.5194/acp-24-9085-2024, 2024
Short summary
Short summary
Cyclones strongly influence weather predictability but still cannot be fully characterised in the Arctic because of the sparse coverage of meteorological measurements. A potential approach to compensate for this is the use of satellite measurements of ozone, because cyclones impact the tropopause and therefore also ozone. In this study we used this connection to investigate the correlation between ozone and the tropopause in the Arctic and to identify cyclones with satellite ozone observations.
Cited articles
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989.
Andersen, H., Cermak, J., Fuchs, J., Knutti, R., and Lohmann, U.: Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks, Atmos. Chem. Phys., 17, 9535–9546, https://doi.org/10.5194/acp-17-9535-2017, 2017.
Andreae, M. O. and Rosenfeld, D.: Aerosol-Cloud-Precipitation Interactions Part 1: The Nature and Sources of Cloud-Active Aerosols, Earth-Sci. Rev., 89, 13–41, https://doi.org/10.1016/j.earscirev.2008.03.001, 2008.
Atmospheric and Environmental Research: RRTMG-SW, GitHub [code], https://github.com/AER-RC/RRTMG_SW (last access: 11 March 2021), 2020.
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A.-L., Dufresne, J.-L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, T., McCoy, D. T., Myhre, G., Mülmenstädt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., and Stevens, B.: Bounding Global Aerosol Radiative Forcing of Climate Change, Rev. Geophys., 58, e2019RG000660, https://doi.org/10.1029/2019rg000660, 2020.
Bender, F. A. M., Frey, L., McCoy, D. T., Grosvenor, D. P., and Mohrmann, J. K.: Assessment of aerosol–cloud–radiation correlations in satellite observations, climate models and reanalysis, Clim. Dynam., 52, 4371–4392, https://doi.org/10.1007/s00382-018-4384-z, 2019.
Bretherton, C. S., Widmann, M., Dymnikov, V. P., Wallace, J. M., and Bladé, I.: Effective Number of Degrees of Freedom of a Spatial Field, J. Climate, 12, 1990–2009 https://doi.org/10.1175/1520-0442(1999)012<1990:TENOSD>2.0.CO;2, 1999.
Bretherton, C. S., Blossey, P. N., and Uchida, J.: Cloud Droplet Sedimentation, Entrainment Efficiency, and Subtropical Stratocumulus Albedo, Geophys. Res. Lett., 34, 1–5, https://doi.org/10.1029/2006GL027648, 2007.
Carslaw, K. S., Lee, L. A., Reddington, C. L., Pringle, K. J., Rap, A., Forster, P. M., Mann, G. W., Spracklen, D. V., Woodhouse, M. T., Regayre, L. A., and Pierce, J. R.: Large contribution of natural aerosols to uncertainty in indirect forcing, Nature, 503, 67–71, https://doi.org/10.1038/nature12674, 2013.
Charlson, R. J., Schwartz, S. E., Hales, J. M., Cess, R. D., Coakley, J. A., Hansen, J. E., and Hofmann, D. J.: Climate Forcing by Anthropogenic Aerosols, Science, 255, 423–430, https://doi.org/10.1126/science.255.5043.423, 1992.
CERES: EBAF_Ed4.1, NASA [data set], https://ceres-tool.larc.nasa.gov/ord-tool/jsp/EBAF42Selection.jsp (last access: 1 January 2023), 2023a.
CERES: FluxByCldTyp_Ed4.1, NASA [data set], https://ceres-tool.larc.nasa.gov/ord-tool/jsp/FluxByCldTypSelection.jsp (last access: 1 January 2023), 2023b.
Chen, Y., Haywood, J., Wang, Y., Malavelle, F., Jordan, G., Partridge, D., Fieldsend, J., De Leeuw, J., Schmidt, A., Cho, N., Oreopoulos, L., Platnick, S., Grosvenor, D., Field, P., and Lohmann, U.: Machine Learning Reveals Climate Forcing from Aerosols is Dominated by Increased Cloud Cover, Nat. Geosci., 15, 609–614, https://doi.org/10.1038/s41561-022-00991-6, 2022.
Chen, Y. C., Christensen, M. W., Stephens, G. L., and Seinfeld, J. H.: Satellite-Based Estimate of Global Aerosol-Cloud Radiative Forcing by Marine Warm Clouds, Nat. Geosci., 7, 643–646, https://doi.org/10.1038/ngeo2214, 2014.
Clough, S. A., Shephard, M. W., Mlawer, E. J., Delamere, J. S., Iacono, M. J., Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric Radiative Transfer Modeling: A Summary of the AER Codes, J. Quant. Spectrosc. Ra., 91, 233–244, https://doi.org/10.1016/j.jqsrt.2004.05.058, 2005.
Dagan, G., Koren, I., Altaratz, O., and Heiblum, R. H.: Time-dependent, non-monotonic response of warm convective cloud fields to changes in aerosol loading, Atmos. Chem. Phys., 17, 7435–7444, https://doi.org/10.5194/acp-17-7435-2017, 2017.
Diamond, M. S., Director, H. M., Eastman, R., Possner, A., and Wood, R.: Substantial Cloud Brightening From Shipping in Subtropical Low Clouds, AGU Adv., 1, 1–28, https://doi.org/10.1029/2019av000111, 2020.
Feingold, G., Goren, T., and Yamaguchi, T.: Quantifying albedo susceptibility biases in shallow clouds, Atmos. Chem. Phys., 22, 3303–3319, https://doi.org/10.5194/acp-22-3303-2022, 2022.
Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J.-L., Frame, D., Lunt, D. J., Mauritsen, T., Palmer, M. D., Watanabe, M., Wild, M., and Zhang, H.: The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896.009, pp. 923–1054, 2021.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L. Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G. K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Ghan, S., Wang, M., Zhang, S., Ferrachat, S., Gettelman, A., Griesfeller, J., Kipling, Z., Lohmann, U., Morrison, H., Neubauer, D., Partridge, D. G., Stier, P., Takemura, T., Wang, H., and Zhang, K.: Challenges in Constraining Anthropogenic Aerosol Effects on Cloud Radiative Forcing using Present-Day Spatiotemporal Variability, P. Natl. Acad. Sci. USA, 113, 5804–5811, https://doi.org/10.1073/pnas.1514036113, 2016.
Glassmeier, F., Hoffmann, F., Johnson, J. S., Yamaguchi, T., Carslaw, K. S., and Feingold, G.: Aerosol-Cloud-Climate Cooling Overestimated by Ship-Track Data, Science, 371, 485–489, https://doi.org/10.1126/science.abd3980, 2021.
Goren, T., Feingold, G., Gryspeerdt, E., Kazil, J., Kretzschmar, J., Jia, H., and Quaas, J.: Projecting Stratocumulus Transitions on the Albedo – Cloud Fraction Relationship Reveals Linearity of Albedo to Droplet Concentrations, Geophys. Res. Lett., 49, e2022GL101169, https://doi.org/10.1029/2022GL101169, 2022.
Goren, T., Sourdeval, O., Kretzschmar, J., and Quaas, J.: Spatial Aggregation of Satellite Observations Leads to an Overestimation of the Radiative Forcing Due To Aerosol-Cloud Interactions, Geophy. Res. Lett., 50, e2023GL105282, https://doi.org/10.1029/2023GL105282, 2023.
Grosvenor, D. P., Sourdeval, O., Zuidema, P., Ackerman, A., Alexandrov, M. D., Bennartz, R., Boers, R., Cairns, B., Chiu, J. C., Christensen, M., Deneke, H., Diamond, M., Feingold, G., Fridlind, A., Hünerbein, A., Knist, C., Kollias, P., Marshak, A., McCoy, D. T, Merk, D., Painemal, D., Rausch, J., Rosenfeld, D., Russchenberg, H., Seifert, P., Sinclair, K., Stier, P., van Diedenhoven, B., Wendisch, M., Werner, F., Wood, R., Zhang, Z., and Quaas, J.: Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives, Rev. Geophys., 56, 409–453, https://doi.org/10.1029/2017RG000593, 2018.
Gryspeerdt, E., Quaas, J., and Bellouin, N.: Constraining the Aerosol Influence on Cloud Fraction, J. Geophys. Res.-Atmos., 121, 3566–3583, https://doi.org/10.1002/2015JD023744, 2016.
Gryspeerdt, E., Goren, T., Sourdeval, O., Quaas, J., Mülmenstädt, J., Dipu, S., Unglaub, C., Gettelman, A., and Christensen, M.: Constraining the aerosol influence on cloud liquid water path, Atmos. Chem. Phys., 19, 5331–5347, https://doi.org/10.5194/acp-19-5331-2019, 2019.
Gryspeerdt, E., Mülmenstädt, J., Gettelman, A., Malavelle, F. F., Morrison, H., Neubauer, D., Partridge, D. G., Stier, P., Takemura, T., Wang, H., Wang, M., and Zhang, K.: Surprising similarities in model and observational aerosol radiative forcing estimates, Atmos. Chem. Phys., 20, 613–623, https://doi.org/10.5194/acp-20-613-2020, 2020.
Gryspeerdt, E., McCoy, D. T., Crosbie, E., Moore, R. H., Nott, G. J., Painemal, D., Small-Griswold, J., Sorooshian, A., and Ziemba, L.: The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data, Atmos. Meas. Tech., 15, 3875–3892, https://doi.org/10.5194/amt-15-3875-2022, 2022a.
Gryspeerdt, E., McCoy, D., Crosbie, E., Moore, R. H., Nott, G. J., Painemal, D., Small-Griswold, J., Sorooshian, A., and Ziemba, L.: Cloud droplet number concentration, calculated from the MODIS cloud optical properties retrieval and gridded using different sampling strategies, NERC EDS Centre for Environmental Data Analysis [data set], https://doi.org/10.5285/864a46cc65054008857ee5bb772a2a2b, 2022b.
IPCC: Annex III: Tables of historical and projected well-mixed greenhouse gas mixing ratios and effective radiative forcing of all climate forcers, edited by: Dentener F. J., Hall, B., and Smith, C., in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou , B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896.017, pp. 2139–2152, 2021.
Jia, H., Ma, X., Yu, F., and Quaas, J.: Significant Underestimation of Radiative Forcing by Aerosol–Cloud Interactions Derived from Satellite-Based Methods, Nat. Commun., 12, 1–11, https://doi.org/10.1038/s41467-021-23888-1, 2021.
Kang, L., Marchand, R. T., Wood, R., and McCoy, I. L.: Coalescence Scavenging Drives Droplet Number Concentration in Southern Ocean Low Clouds, Geophys. Res. Lett., 49, 1–10, https://doi.org/10.1029/2022GL097819, 2022.
Kinne, S.: Aerosol radiative effects with MACv2, Atmos. Chem. Phys., 19, 10919–10959, https://doi.org/10.5194/acp-19-10919-2019, 2019.
Kramer, R. J., He, H., Soden, B. J., Oreopoulos, L., Myhre, G., Forster, P. M., and Smith, C. J.: Observational Evidence of Increasing Global Radiative Forcing, Geophys. Res. Lett., 48, 1–11, https://doi.org/10.1029/2020GL091585, 2021.
Lewis, H., Bellon, G., and Dinh, T.: Upstream Large-Scale Control of Subtropical Low-Cloud Climatology, J. Climate, 36, 3289–3303, https://doi.org/10.1175/JCLI-D-22-0676.1, 2023.
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G., Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the Earth's Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product, J. Climate, 31, 895–918, https://doi.org/10.1175/JCLI-D-17-0208.1, 2018.
Ma, P., Rasch, P. J., Chepfer, H., Winker, D. M., and Ghan, S. J.: Observational Constraint on Cloud Susceptibility Weakened by Aerosol Retrieval Limitations, Nat. Commun., 9, 1–10, https://doi.org/10.1038/s41467-018-05028-4, 2018.
Manshausen, P., Watson-Parris, D., Christensen, M. W., Jalkanen, J. P., and Stier, P.: Invisible ship tracks show large cloud sensitivity to aerosol, Nature, 610, 101–106, https://doi.org/10.1038/s41586-022-05122-0, 2022.
Matthews, H. D. and Zickfeld, K.: Climate Response to Zeroed Emissions of Greenhouse Gases and Aerosols, Nat. Clim. Change, 2, 338–341, https://doi.org/10.1038/nclimate1424, 2012.
Mauger, G. S. and Norris, J. R.: Meteorological Bias in Satellite Estimates of Aerosol-Cloud Relationships, Geophys. Res. Lett., 34, 1–5, https://doi.org/10.1029/2007GL029952, 2007.
Mauritsen, T. and Pincus, R.: Committed Warming Inferred from Observations, Nat. Clim. Change, 7, 652–655, https://doi.org/10.1038/nclimate3357, 2017.
McCoy, D. T., Bender, F. A. M., Mohrmann, J. K. C., Hartmann, D. L., Wood, R., and Grosvenor, D. P.: The global aerosol-cloud first indirect effect estimated using MODIS, MERRA, and AeroCom. J. Geophys. Res.- Atmos., 122, 1779–1796, https://doi.org/10.1002/2016JD026141, 2017.
McCoy, D. T., Field, P. R., Schmidt, A., Grosvenor, D. P., Bender, F. A.-M., Shipway, B. J., Hill, A. A., Wilkinson, J. M., and Elsaesser, G. S.: Aerosol midlatitude cyclone indirect effects in observations and high-resolution simulations, Atmos. Chem. Phys., 18, 5821–5846, https://doi.org/10.5194/acp-18-5821-2018, 2018.
Myers, T. A., Scott, R. C., Zelinka, M. D., Klein, S. A., Norris, J. R., and Caldwell, P. M.: Observational Constraints on Low Cloud Feedback Reduce Uncertainty of Climate Sensitivity, Nat. Clim. Change, 11, 501–507, https://doi.org/10.1038/s41558-021-01039-0, 2021.
NASA: MERRA-2, Goddard Earth Sciences Data and Information Services Center [data set], https://doi.org/10.5067/LTVB4GPCOTK2, 2023a.
NASA: MCD06COSP_M3_MODIS – MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid, Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MCD06COSP_M3_MODIS.062, 2023b.
Naud, C. M., Posselt, D. J., and van den Heever, S. C.: Observed Covariations of Aerosol Optical Depth and Cloud Cover in Extratropical Cyclones, J. Geophys. Res.-Atmos., 122, 10338–10356, https://doi.org/10.1002/2017JD027240, 2017.
Painemal, D., Chiu, J.-Y. C., Minnis, P., Yost, C., Zhou, X., Cadeddu, M., Eloranta, E., Lewis, E. R., Ferrare, R., and Kollias, P.: Aerosol and Cloud Microphysics Covariability in the Northeast Pacific Boundary Layer Estimated with Ship-Based and Satellite Remote Sensing Observations, J. Geophys. Res.-Atmos., 122, 2403–2418, https://doi.org/10.1002/2016JD025771, 2017.
Painemal, D. and Zuidema, P.: Assessment of MODIS Cloud Effective Radius and Optical Thickness Retrievals over the Southeast Pacific with VOCALS-REx In Situ Measurements, J. Geophys. Res.-Atmos., 116, 1–16, https://doi.org/10.1029/2011JD016155, 2011.
Pincus, R. and Baker, M. B.: Effect of Precipitation on the Albedo Susceptibility of Clouds in the Marine Boundary Layer, Nature, 372, 250–252, https://doi.org/10.1038/372250a0, 1994.
Pincus, R., Hubanks, P. A., Platnick, S., Meyer, K., Holz, R. E., Botambekov, D., and Wall, C. J.: Updated observations of clouds by MODIS for global model assessment, Earth Syst. Sci. Data, 15, 2483–2497, https://doi.org/10.5194/essd-15-2483-2023, 2023.
Platnick, S.: Vertical Photon Transport in Cloud Remote Sensing Problems, J. Geophys. Res.-Atmos., 105, 22919–22935, https://doi.org/10.1029/2000JD900333, 2000.
Platnick, S., Ackerman, S., and King, M.: MODIS Atmosphere L2 Cloud Product (06_L2). NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA, https://doi.org/10.5067/MODIS/MOD06_L2.061, 2015.
Platnick, S., Meyer, K. G., King, M. D., Wind, G., Amarasinghe, N., Marchant, B., Arnold, G. T., Zhang, Z., Hubanks, P. A., Holz, R. E., Yang, P., Ridgway, W. L., and Reidi, J.: The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples from Terra and Aqua, IEEE T. Geosci. Remote, 3, 163–186, https://doi.org/10.1109/TGRS.2016.2610522, 2017.
Possner, A., Wang, H., Wood, R., Caldeira, K., and Ackerman, T. P.: The efficacy of aerosol–cloud radiative perturbations from near-surface emissions in deep open-cell stratocumuli, Atmos. Chem. Phys., 18, 17475–17488, https://doi.org/10.5194/acp-18-17475-2018, 2018.
Possner, A., Eastman, R., Bender, F., and Glassmeier, F.: Deconvolution of boundary layer depth and aerosol constraints on cloud water path in subtropical stratocumulus decks, Atmos. Chem. Phys., 20, 3609–3621, https://doi.org/10.5194/acp-20-3609-2020, 2020.
Raghuraman, S. P., Paynter, D., and Ramaswamy, V.: Anthropogenic forcing and response yield observed positive trend in Earth's energy imbalance, Nat. Commun., 12, 1–10, https://doi.org/10.1038/s41467-021-24544-4, 2021.
Randles, C. A., da Silva, A. M., Buchard, V., Colarco, P. R., Darmenov, A., Govindaraju, R., Smirnov, A., Holben, B., Ferrare, R., Hair, J., Shinozuka, Y., and Flynn, C. J.: The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data Assimilation Evaluation, J. Climate, 30, 6823–6850, https://doi.org/10.1175/JCLI-D-16-0609.1, 2017.
Rosenfeld, D., Kaufman, Y. J., and Koren, I.: Switching cloud cover and dynamical regimes from open to closed Benard cells in response to the suppression of precipitation by aerosols, Atmos. Chem. Phys., 6, 2503–2511, https://doi.org/10.5194/acp-6-2503-2006, 2006.
Rosenfeld, D., Andreae, M. O., Asmi, A., Chin, M., Leeuw, G., Donovan, D. P., Kahn, R., Kinne, S., Kivekäs, N., Kulmala, M., Lau, W., Schmidt, S. K., Suni, T., Wagner, T., Wild, M., and Quaas, J.: Global Observations of Aerosol-Cloud-Precipitation-Climate Interactions. Rev. Geophys., 52, 750–808, https://doi.org/10.1002/2013RG000441, 2014.
Rosenfeld, D., Zhu, Y., Wang, M., Zheng, Y., Goren, T., and Yu, S.: Aerosol-Driven Droplet Concentrations Dominate Coverage and Water of Oceanic Low-Level Clouds, Science, 363, eaav0566, https://doi.org/10.1126/science.aav0566, 2019.
Scott, R. C., Myers, T. A., Norris, J. R., Zelinka, M. D., Klein, S. A., Sun, M., and Doelling, D. R.: Observed Sensitivity of Low-Cloud Radiative Effects to Meteorological Perturbations over the Global Oceans, J. Climate, 33, 7717–7734, https://doi.org/10.1175/JCLI-D-19-1028.1, 2020.
Seifert, A., Heus, T., Pincus, R., and Stevens, B.: Large-Eddy Simulation of the Transient and Near-Equilibrium Behavior of Precipitating Shallow Convection, J. Adv. Model. Earth Sy., 6, 513–526, https://doi.org/10.1002/2015MS000470, 2015.
Sherwood, S. C., Webb, M. J., Annan, J. D., Armour, K. C., Forster, P. M., Hargreaves, J. C., Hegerl, G., Klein, S. A., Marvel, K. D., Rohling, E. J., Watanabe, M., Andrews, T., Braconnot, P., Bretherton, C. S., Foster, G. L., Hausfather, Z., von der Heydt, A. S., Knutti, R., Mauritsen, T., Norris, J. R., Proistosescu, C., Rugenstein, M., Schmidt, G. A., Tokarska, K. B., and Zelinka, M. D.: An Assessment of Earth's Climate Sensitivity Using Multiple Lines of Evidence. Rev. Geophys., 58, 1–92, https://doi.org/10.1029/2019RG000678, 2020.
Small, J. D., Chuang, P. Y., Feingold, G., and Jiang, H.: Can Aerosol Decrease Cloud Lifetime? Geophys. Res. Lett., 36, 1–5, https://doi.org/10.1029/2009GL038888, 2009.
Smith, C. J., Harris, G. R., Palmer, M. D., Bellouin, N., Collins, W., Myhre, G., Schulz, M., Golaz, J. C., Ringer, M., Storelvmo, T., and Forster, P. M.: Energy Budget Constraints on the Time History of Aerosol Forcing and Climate Sensitivity, J. Geophys. Res.-Atmos., 126, 1–20, https://doi.org/10.1029/2020JD033622, 2021.
Smith, S. J., van Aardenne, J., Klimont, Z., Andres, R. J., Volke, A., and Delgado Arias, S.: Anthropogenic sulfur dioxide emissions: 1850–2005, Atmos. Chem. Phys., 11, 1101–1116, https://doi.org/10.5194/acp-11-1101-2011, 2011.
Stevens, B.: Rethinking the Lower Bound on Aerosol Radiative Forcing, J. Climate, 28, 4794–4819, https://doi.org/10.1175/JCLI-D-14-00656.1, 2015.
Sun, M., Doelling, D. R., Loeb, N. G., Scott, R. C., Wilkins, J., Nguyen, L. T., and Mlynczak, P.: Clouds and the Earth's Radiant Energy System (CERES) FluxByCldTyp Edition 4 Data Product, J. Atmos. Ocean. Tech., 39, 303–318, https://doi.org/10.1175/jtech-d-21-0029.1, 2022.
Toll, V., Christensen, M., Quaas, J., and Bellouin, N.: Weak average liquid-cloud-water response to anthropogenic aerosols, Nature, 572, 51–55, https://doi.org/10.1038/s41586-019-1423-9, 2019.
Twomey, S.: Influence of Pollution on Shortwave Albedo of Clouds, J. Atmos. Sci., 34, 1149–1152, https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2, 1977.
Wall, C. J.: MODIS Re-LWP cloud radiative kernel, GitHub [data set], https://github.com/caseywall7926/MODIS_Re-LWP_kernel (last access: 10 October 2023), 2023a.
Wall, C. J.: caseywall7926/MODIS_Re-LWP_kernel: MODIS Re-LWP cloud radiative kernel (v1.0), Zenodo, https://doi.org/10.5281/zenodo.8427293, 2023b.
Wall, C. J., Norris, J. R., Possner, A., McCoy, D. T., McCoy, I. L., and Lutsko, N. J.: Assessing Effective Radiative Forcing from Aerosol–Cloud Interactions over the Global Ocean, P. Natl. Acad. Sci. USA, 119, https://doi.org/10.1073/pnas.2210481119, 2022.
Watson-Parris, D. and Smith, C. J.: Large uncertainty in future warming due to aerosol forcing, Nat. Clim. Change, 12, 1111–1113, https://doi.org/10.1038/s41558-022-01516-0, 2022.
WCRP: CMIP6 historical simulations, CMIP6 online archive [data set], https://esgf-node.llnl.gov/projects/cmip6/ (last access: 1 May 2022), 2022.
Wilks, D. S.: “The Stippling Shows Statistically Significant Grid Points.” How Research Results are Routinely Overstated and Overinterpreted, and What to Do about It, B. Am. Meteorol. Soc., 97, 2263–2274, https://doi.org/10.1175/BAMS-D-15-00267.1, 2016.
Wood, R. and Bretherton, C. S.: On the Relationship Between Stratiform Low Cloud Cover and Lower-Tropospheric Stability, J. Climate, 19, 6425–6432, https://doi.org/10.1175/JCLI3988.1, 2006.
Wood, R., Leon, D., Lebsock, M., Snider, J., and Clarke, A. D.: Precipitation Driving of Droplet Concentration Variability in Marine Low Clouds, J. Geophys. Res.-Atmos., 117, 1–11, https://doi.org/10.1029/2012JD018305, 2012.
Zelinka, M. D., Klein, S. A., and Hartmann, D. L.: Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels, J. Climate, 25, 3715–3735, https://doi.org/10.1175/JCLI-D-11-00248.1, 2012.
Zelinka, M. D., Klein, S. A., Taylor, K. E., Andrews, T., Webb, M. J., Gregory, J. M., and Forster, P. M.: Contributions of Different Cloud Types to Feedbacks and Rapid Adjustments in CMIP5, J. Climate, 26, 5007–5027, https://doi.org/10.1175/JCLI-D-12-00555.1, 2013.
Zelinka, M. D., Andrews, T., Forster, P. M., and Taylor, K. E.: Quantifying Components of Aerosol-Cloud-Radiation Interactions in Climate Models, J. Geophys. Res.-Atmos., 119, 7599–7615, https://doi.org/10.1002/2014JD021710, 2014.
Zhang, J. and Feingold, G.: Distinct regional meteorological influences on low-cloud albedo susceptibility over global marine stratocumulus regions, Atmos. Chem. Phys., 23, 1073–1090, https://doi.org/10.5194/acp-23-1073-2023, 2023.
Zhang, J., Zhou, X., Goren, T., and Feingold, G.: Albedo susceptibility of northeastern Pacific stratocumulus: the role of covarying meteorological conditions, Atmos. Chem. Phys., 22, 861–880, https://doi.org/10.5194/acp-22-861-2022, 2022.
Zhang, Z. and Platnick, S.: An Assessment of Differences Between Cloud Effective Particle Radius Retrievals for Marine Water Clouds from three MODIS Spectral Bands, J. Geophys. Res.-Atmos., 116, 1–19, https://doi.org/10.1029/2011JD016216, 2011.
Zhou, X., Zhang, J., and Feingold, G.: On the Importance of Sea Surface Temperature for Aerosol-Induced Brightening of Marine Clouds and Implications for Cloud Feedback in a Future Warmer Climate, Geophys. Res. Lett., 48, https://doi.org/10.1029/2021GL095896, 2021.
Zhu, Y., Rosenfeld, D., and Li, Z.: Under What Conditions Can We Trust Retrieved Cloud Drop Concentrations in Broken Marine Stratocumulus? J. Geophys. Res. Atmos., 123, 8754–8767, https://doi.org/10.1029/2017JD028083, 2018.
Executive editor
One of the largest sources of uncertainty in the overall anthropogenic forcing of climate is still the aerosol impact on liquid clouds. Disentangling the various aerosol-cloud interactions helps to improve estimates of the magnitude of global warming in the future. The current study provides the most rigorous method to date in assessing the aerosol radiative effects from satellite observations across the global ocean. The aerosol responses are decomposed into the Twomey effect (cooling due to an increase in cloud-droplet number concentration), and the adjustments of the cloud liquid water path and cloud fraction (often analysed separately) at a near-global scale. The total effective radiative forcing of liquid clouds since 1850 has been found to be negative, with the cloud adjustments larger than the Twomey effect, which was previously thought to be larger.
One of the largest sources of uncertainty in the overall anthropogenic forcing of climate is...
Short summary
Interactions between aerosol pollution and liquid clouds are one of the largest sources of uncertainty in the effective radiative forcing of climate over the industrial era. We use global satellite observations to decompose the forcing into components from changes in cloud-droplet number concentration, cloud water content, and cloud amount. Our results reduce uncertainty in these forcing components and clarify their relative importance.
Interactions between aerosol pollution and liquid clouds are one of the largest sources of...
Altmetrics
Final-revised paper
Preprint