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the claim
Clouds have a measurable physical size distribution
the verdict
SUPPORTED
the evidence backs this
Recorded sources
11 sources for · 0 against
Is it true that clouds have a measurable physical size distribution?
Yes. Numerous scientific studies and remote-sensing campaigns routinely measure, parameterize, and map the physical size distribution and effective radius of cloud droplets.
Verdict: SUPPORTED · 11 sources for, 0 against · Last checked
The analysis
The claim asserts that clouds have a measurable physical size distribution. Multiple peer-reviewed studies across remote sensing, field campaigns, and in situ measurements explicitly measure, retrieve, and evaluate cloud droplet size distributions (DSD), effective radius, and effective variance. The evidence overwhelmingly supports the claim.
Evidence for · 11
Analyzes cloud droplet size distributions and their spectral dispersion parameterizations.
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Liu, Y. & Daum, P. H. (2000). Spectral dispersion of cloud droplet size distributions and the parameterization of cloud droplet effective radius. doi.org. https://doi.org/10.1029/1999gl011011
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More for · 10
Derives an analytic cloud droplet effective radius expression dependent on droplet spectral distribution.
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Pontikis, C. & Hicks, E. (1992). Contribution to the cloud droplet effective radius parameterization. doi.org. https://doi.org/10.1029/92gl02283
Measures cloud droplet size distribution properties and variance to map spatial heterogeneity.
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Mcbride, B., Martins, J., Barbosa, H., Birmingham, W., & Remer, L. (2019). Spatial distribution of cloud droplet size properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) measurements. doi.org. https://doi.org/10.5194/amt-2019-380
Retrieves cloud droplet size distribution and effective variance using polarized measurements.
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Shang, H., Letu, H., Bréon, F., Riedi, J., Ma, R., Wang, Z., Nakajima, T., Wang, Z., & Chen, L. (2019). An improved algorithm of cloud droplet size distribution from POLDER polarized measurements. doi.org. https://doi.org/10.1016/J.RSE.2019.04.013
Maps cloud droplet size distribution, effective radius, and effective variance at high spatial resolution.
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Pörtge, V., Kölling, T., Weber, A., Volkmer, L., Emde, C., Zinner, T., Forster, L., & Mayer, B. (2023). High-spatial-resolution retrieval of cloud droplet size distribution from polarized observations of the cloudbow. doi.org. https://doi.org/10.5194/amt-16-645-2023
Evaluates liquid cloud droplet effective radius from drop size distributions using multiple sensing methods.
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Fu, D., Girolamo, L. D., Rauber, R., McFarquhar, G., Nesbitt, S., Loveridge, J., Hong, Y., Diedenhoven, B. v., Cairns, B., Alexandrov, M., Lawson, P., Woods, S., Tanelli, S., Sy, O., Schmidt, S., Hostetler, C., & Scarino, A. (2022). An evaluation of liquid cloud droplet effective radius derived from MODIS, airborne remote sensing and in situ measurements from CAMP2Ex. doi.org. https://doi.org/10.5194/acp-2022-73
Examines droplet size distribution broadening and properties in warm stratiform clouds.
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Sinclair, K., Diedenhoven, B. v., Cairns, B., Alexandrov, M., Dzambo, A. M., & L’Ecuyer, T. (2021). Inference of Precipitation in Warm Stratiform Clouds Using Remotely Sensed Observations of the Cloud Top Droplet Size Distribution. doi.org. https://doi.org/10.1029/2021GL092547
Derives particle size distributions in terms of cloud effective radius and effective variance from polarized measurements.
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Volkmer, L., Pörtge, V., Jakub, F., & Mayer, B. (2024). Model-based evaluation of cloud geometry and droplet size retrievals from two-dimensional polarized measurements of specMACS. doi.org. https://doi.org/10.5194/amt-17-1703-2024
Compares spectral cloud effective radius and droplet size distributions from airborne and in situ observations.
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Meyer, K., Platnick, S., Arnold, G., Amarasinghe, N., Miller, D., Small-Griswold, J. D., Witte, M. K., Cairns, B., Gupta, S., McFarquhar, G., & O’Brien, J. (2025). Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES. doi.org. https://doi.org/10.5194/amt-18-981-2025
Estimates cloud droplet effective radius profiles linked to droplet size characteristics.
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Zang, L., Rosenfeld, D., Mao, F., Pan, Z., Zhu, Y., Gong, W., & Wang, Z. (2021). CALIOP retrieval of droplet effective radius accounting for cloud vertical homogeneity.. doi.org. https://doi.org/10.1364/OE.427022
Develops a cloud droplet effective radius retrieval algorithm tied to cloud droplet size distribution assumptions.
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Du, J., Ge, J., Zhang, C., Su, J., Hu, X., Zhu, Z., Li, Q., Huang, J., & Fu, Q. (2024). An Accurate Retrieval of Cloud Droplet Effective Radius for Single-Wavelength Cloud Radar. doi.org. https://doi.org/10.1109/TGRS.2024.3447002
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What does the evidence say?
The claim asserts that clouds have a measurable physical size distribution. Multiple peer-reviewed studies across remote sensing, field campaigns, and in situ measurements explicitly measure, retrieve, and evaluate cloud droplet size distributions (DSD), effective radius, and effective variance. The evidence overwhelmingly supports the claim.
Receipt History
first checked05 Aug 2026
judged → SUPPORTED · 8705 Aug 2026
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