Articles | Volume 26, issue 15
https://doi.org/10.5194/acp-26-11281-2026
© Author(s) 2026. 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-26-11281-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Aug 2026
Research article |
| 12 Aug 2026
| 12 Aug 2026
Process evaluation suggests models misrepresent the precipitation-driven replenishment of cloud condensation nuclei
Sara M. Blichner
CORRESPONDING AUTHOR
Department of Environmental Science, Stockholm University, Stockholm, 10691, Sweden
Bolin Centre for Climate research, Stockholm University, Stockholm, 10691, Sweden
Theodore Khadir
Department of Environmental Science, Stockholm University, Stockholm, 10691, Sweden
Bolin Centre for Climate research, Stockholm University, Stockholm, 10691, Sweden
Sini Talvinen
Department of Environmental Science, Stockholm University, Stockholm, 10691, Sweden
Bolin Centre for Climate research, Stockholm University, Stockholm, 10691, Sweden
Department of Technical Physics, University of Eastern Finland, Kuopio, 70211, Finland
Paulo Artaxo
Instituto de Física, Universidade de São Paulo, São Paulo, Brazil
Liine Heikkinen
Department of Environmental Science, Stockholm University, Stockholm, 10691, Sweden
Bolin Centre for Climate research, Stockholm University, Stockholm, 10691, Sweden
Harri Kokkola
Department of Technical Physics, University of Eastern Finland, Kuopio, 70211, Finland
Finnish Meteorological Institute, Kuopio, 70211, Finland
Radovan Krejci
Department of Environmental Science, Stockholm University, Stockholm, 10691, Sweden
Bolin Centre for Climate research, Stockholm University, Stockholm, 10691, Sweden
Muhammed Irfan
Department of Technical Physics, University of Eastern Finland, Kuopio, 70211, Finland
Institute of Chemical Engineering Sciences (ICE-HT), Foundation for Research and Technology – Hellas (FORTH), Patras, Greece
School of Architecture, Civil and Environmental Engineering (ENAC), Laboratory of Atmospheric Processes and their Impacts (LAPI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Twan van Noije
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Tuukka Petäjä
University of Helsinki, Institute for Atmospheric and Earth System Research (INAR), Helsinki, 00014, Finland
Christopher Pöhlker
Multiphase Chemistry Department, Max Planck Institute for Chemistry, 55128 Mainz, Germany
Øyvind Seland
Norwegian Meteorological Institute, Oslo, Norway
Carl Svenhag
Department of Physics, Lund University, Lund, Sweden
now at: Department of Environmental Science, Aarhus University, Roskilde, Denmark
Antti Vartiainen
Department of Technical Physics, University of Eastern Finland, Kuopio, 70211, Finland
Advanced Computing Facility, CSC – IT Center for Science Ltd, Espoo, 02150, Finland
Ilona Riipinen
Department of Environmental Science, Stockholm University, Stockholm, 10691, Sweden
Bolin Centre for Climate research, Stockholm University, Stockholm, 10691, Sweden
Data sets
Trajectory precipitation and station data for three GCMs and for observations S. Blichner https://doi.org/10.5281/zenodo.15528150
PNSDs and Trajectory History Datasets (Khadir et al., 2023) T. Khadir https://doi.org/10.5281/zenodo.7907473
Model code and software
Sarambl/PRCP2SZDST: Release 1 Sara Blichner https://doi.org/10.5281/zenodo.21701735
Short summary
This study looks at how well climate models capture the impact of rain on particles that help form cloud droplets. Using data from three measurement stations and applying both a correlation analysis and a machine learning approach, we found that models often miss how new particles form after rain and struggle in cold environments. This matters because these particles influence cloud formation and climate.
This study looks at how well climate models capture the impact of rain on particles that help...
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