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| 科勒理论× | 云凝结核分析× | 谱格微物理方案× | |
|---|---|---|---|
| 领域 | 气象学 | 气象学 | 气象学 |
| 方法族 | Process / pipeline | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1936 | 1959 | 1999 |
| 提出者≠ | Hilding Kohler | Twomey, Woodard | Khain, Ovtchinnikov |
| 类型≠ | Thermodynamic equilibrium framework | Cloud microphysical measurement | Explicit particle size distribution model |
| 开创性文献≠ | Köhler, H. (1936). The nucleus in and the growth of hygroscopic droplets. Transactions of the Faraday Society, 32, 1152-1161. DOI ↗ | Dusek, U., Frank, G. P., Hildebrandt, L., et al. (2006). Size matters more than chemistry for cloud-nucleating ability of aerosol particles. Science, 312(5778), 1375-1378. DOI ↗ | Khain, A. P., Ovtchinnikov, M., Pinsky, M., Pokrovsky, A., & Krugliak, H. (2000). Notes on the state-of-the-art numerical modeling of cloud microphysics. Atmospheric Research, 55(3–4), 159-224. DOI ↗ |
| 别名 | Kohler theory, Kohler equilibrium, Cloud droplet nucleation | CCN analysis, Cloud condensation nuclei, CCN measurement | Bin microphysics, Spectral microphysics, Explicit microphysics |
| 相关 | 3 | 3 | 3 |
| 摘要≠ | Köhler theory is a foundational framework in cloud microphysics that predicts the equilibrium supersaturation required for an aerosol particle of given size and composition to grow into a cloud droplet. Published in 1936 by Hilding Köhler, it combines the Kelvin effect (vapor pressure enhancement over curved surfaces) with the Raoult effect (vapor pressure depression from dissolved solute) to explain cloud droplet formation. | Cloud condensation nuclei (CCN) analysis examines the number and properties of aerosol particles capable of nucleating cloud droplets at various supersaturation levels. This field involves measuring CCN concentrations, characterizing their chemical composition and size, and relating aerosol properties to cloud microphysical processes. | Spectral bin microphysics is a detailed cloud microphysical modeling approach that explicitly represents the particle size distribution (PSD) by dividing particles into discrete size bins. Rather than assuming a fixed shape for the PSD, bin models track the number and mass of particles in each size category, allowing detailed simulation of cloud and precipitation processes. |
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