1. Seasonal Variations, Origin, and Parameterization of Ice‐Nucleating Particles at a Mountain Station in Central France
- Author
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Yannick Bras, Evelyn Freney, Antoine Canzi, Pierre Amato, Laetitia Bouvier, Jean‐Marc Pichon, David Picard, María Cruz Minguillón, Noemí Pérez, and Karine Sellegri
- Subjects
ice nuclei particles ,nucleation ,clouds ,aerosols ,mountain site ,Astronomy ,QB1-991 ,Geology ,QE1-996.5 - Abstract
Abstract Identifying how aerosol particles interact with atmospheric water is critical to understand climate and precipitation. Ice‐nucleating particles (INP) trigger the formation of atmospheric ice crystals at higher temperatures than pure water. They are difficult to characterize because of their scarce occurrence, and variability, in the atmosphere, especially at temperatures above −20°C. It has been demonstrated that at these temperatures, biological aerosol particles can contribute significantly to INP number concentration. This study incorporates a series of offline, size‐segregated measurements of INPs collected at the Puy de Dôme station (PUY, 1,465 m a.s.l.) over a 6 month period from October to May, covering the transitions from autumn, winter, to spring. These measurements show a general trend of decreasing particle number concentrations during the winter months and higher concentration during autumn and spring. INP concentrations measured in the range of −5 and −18°C, had concentrations of 0.001 INP/Lair at the warmest temperatures, and between 0.01 and 0.1 INP/Lair at the coldest temperatures. The majority of INP measured at temperatures warmer than −15°C were heat labile, suggesting a biological or organic origin. The INP variability was compared with collocated aerosol physical and chemical properties, allowing us to associate highest INP concentrations with local and marine origins. Following these comparisons, we use aerosol total number concentration to develop a new parameterization. In addition, this parameterization is specifically optimized for warmer temperature INP measurements, and demonstrated a good performance when tested on independent data sets.
- Published
- 2024
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