Articles | Volume 24, issue 23
https://doi.org/10.5194/acp-24-13371-2024
© Author(s) 2024. 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-24-13371-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Dec 2024
Research article |
| 04 Dec 2024
| 04 Dec 2024
Constraining net long-term climate feedback from satellite-observed internal variability possible by the mid-2030s
Alejandro Uribe
CORRESPONDING AUTHOR
Department of Meteorology, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm, Sweden
Frida A.-M. Bender
Department of Meteorology, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm, Sweden
Thorsten Mauritsen
Department of Meteorology, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm, Sweden
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Peter Kuma, Frida A.-M. Bender, Alex Schuddeboom, Adrian J. McDonald, and Øyvind Seland
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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.
James D. Annan, Julia C. Hargreaves, and Thorsten Mauritsen
Clim. Past, 18, 1883–1896, https://doi.org/10.5194/cp-18-1883-2022, https://doi.org/10.5194/cp-18-1883-2022, 2022
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We have created a new global surface temperature reconstruction of the climate of the Last Glacial Maximum, representing the period 19–23 000 years before the present day. We find that the globally averaged mean temperature was roughly 4.5 °C colder than it was in pre-industrial times, albeit there is significant uncertainty on this value.
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.
Jule Radtke, Thorsten Mauritsen, and Cathy Hohenegger
Atmos. Chem. Phys., 21, 3275–3288, https://doi.org/10.5194/acp-21-3275-2021, https://doi.org/10.5194/acp-21-3275-2021, 2021
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Shallow trade wind clouds are a key source of uncertainty to projections of the Earth's changing climate. We perform high-resolution simulations of trade cumulus and investigate how the representation and climate feedback of these clouds depend on the specific grid spacing. We find that the cloud feedback is positive when simulated with kilometre but near zero when simulated with hectometre grid spacing. These findings suggest that storm-resolving models may exaggerate the trade cloud feedback.
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
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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.
Martin Renoult, James Douglas Annan, Julia Catherine Hargreaves, Navjit Sagoo, Clare Flynn, Marie-Luise Kapsch, Qiang Li, Gerrit Lohmann, Uwe Mikolajewicz, Rumi Ohgaito, Xiaoxu Shi, Qiong Zhang, and Thorsten Mauritsen
Clim. Past, 16, 1715–1735, https://doi.org/10.5194/cp-16-1715-2020, https://doi.org/10.5194/cp-16-1715-2020, 2020
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Interest in past climates as sources of information for the climate system has grown in recent years. In particular, studies of the warm mid-Pliocene and cold Last Glacial Maximum showed relationships between the tropical surface temperature of the Earth and its sensitivity to an abrupt doubling of atmospheric CO2. In this study, we develop a new and promising statistical method and obtain similar results as previously observed, wherein the sensitivity does not seem to exceed extreme values.
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Short summary
Our study explores climate feedbacks, vital for understanding global warming. It links them to shifts in Earth's energy balance at the atmosphere's top due to natural temperature variations. It takes roughly 50 years to establish this connection. Combined satellite observations and reanalysis suggest that Earth cools more than expected under carbon dioxide influence. However, continuous satellite data until at least the mid-2030s are crucial for refining our understanding of climate feedbacks.
Our study explores climate feedbacks, vital for understanding global warming. It links them to...
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