Articles | Volume 25, issue 6
https://doi.org/10.5194/acp-25-3841-2025
https://doi.org/10.5194/acp-25-3841-2025
Research article
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02 Apr 2025
Research article | Highlight paper |  | 02 Apr 2025

Pristine oceans are a significant source of uncertainty in quantifying global cloud condensation nuclei

Goutam Choudhury, Karoline Block, Mahnoosh Haghighatnasab, Johannes Quaas, Tom Goren, and Matthias Tesche

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Cited articles

Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present), J. Hydrometeorol., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003. a
Alexandri, F., Müller, F., Choudhury, G., Achtert, P., Seelig, T., and Tesche, M.: A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations, Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, 2024. a
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Aravindhavel, A., Choudhury, G., Prabhakaran, T., Murugavel, P., and Tesche, M.: Retrieval and validation of cloud condensation nuclei from satellite and airborne measurements over the Indian Monsoon region, Atmos. Res., 290, 106802, https://doi.org/10.1016/j.atmosres.2023.106802, 2023. a, b
Asmi, E., Kondratyev, V., Brus, D., Laurila, T., Lihavainen, H., Backman, J., Vakkari, V., Aurela, M., Hatakka, J., Viisanen, Y., Uttal, T., Ivakhov, V., and Makshtas, A.: Aerosol size distribution seasonal characteristics measured in Tiksi, Russian Arctic, Atmos. Chem. Phys., 16, 1271–1287, https://doi.org/10.5194/acp-16-1271-2016, 2016. a
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Executive editor
Measurement datasets of cloud condensation nuclei (CCN) are vital for our understanding of aerosol-cloud interaction and reliable climate modelling. This study analyses and compares the only two global CCN datasets derived from satellite and reanalysis data. These key datasets are found to disagree over pristine oceans in terms of their climatology as well as seasonal and annual variations. Given the importance of CCN as a fundamental property in climate model simulations, further research is needed to reconcile these differences and to produce an observation-based dataset that can be confidently used to evaluate our understanding.
Short summary
Aerosol particles in the atmosphere increase cloud reflectivity, thereby cooling the Earth. Accurate global measurements of these particles are crucial for estimating this cooling effect. This study compares and harmonizes two newly developed global aerosol datasets, offering insights for their future use and refinement. We identify pristine oceans as a significant source of uncertainty in the datasets and, therefore, in quantifying the role of aerosols in Earth's climate.
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