Articles | Volume 17, issue 12
https://doi.org/10.5194/essd-17-6943-2025
https://doi.org/10.5194/essd-17-6943-2025
Data description paper
 | 
09 Dec 2025
Data description paper |  | 09 Dec 2025

Long-term measurements of ice nucleating particles at Atmospheric Radiation Measurement (ARM) sites worldwide

Jessie M. Creamean, Carson C. Hume, Maria Vazquez, and Adam Theisen

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Cited articles

Agresti, A. and Coull, B. A.: Approximate Is Better than “Exact” for Interval Estimation of Binomial Proportions, Am. Stat., 52, 119, https://doi.org/10.2307/2685469, 1998. 
Barry, K. R., Hill, T. C. J., Jentzsch, C., Moffett, B. F., Stratmann, F., and DeMott, P. J.: Pragmatic protocols for working cleanly when measuring ice nucleating particles, Atmos. Res., 250, 105419, https://doi.org/10.1016/j.atmosres.2020.105419, 2021. 
Barry, K. R., Hill, T. C. J., Nieto-Caballero, M., Douglas, T. A., Kreidenweis, S. M., DeMott, P. J., and Creamean, J. M.: Active thermokarst regions contain rich sources of ice-nucleating particles, Atmos. Chem. Phys., 23, 15783–15793, https://doi.org/10.5194/acp-23-15783-2023, 2023a. 
Barry, K. R., Hill, T. C. J., Moore, K. A., Douglas, T. A., Kreidenweis, S. M., DeMott, P. J., and Creamean, J. M.: Persistence and Potential Atmospheric Ramifications of Ice-Nucleating Particles Released from Thawing Permafrost, Environ. Sci. Technol., 57, 3505–3515, https://doi.org/10.1021/acs.est.2c06530, 2023b. 
Barry, K. R., Hill, T. C. J., Kreidenweis, S. M., DeMott, P. J., Tobo, Y., and Creamean, J. M.: Bioaerosols as indicators of central Arctic ice nucleating particle sources, Atmos. Chem. Phys., 25, 11919–11933, https://doi.org/10.5194/acp-25-11919-2025, 2025. 
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Short summary
This study presents a comprehensive, publicly available ice nucleating particles (INP) dataset from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility across diverse environments, including Arctic, agricultural, urban, marine, and mountainous sites. Samples are collected via fixed and mobile platforms and processed using a standardized pipeline. The dataset supports observational and modelling analyses of seasonal, spatial, and compositional variability in INPs.
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