Tomasz Ściężor · Journal of Quantitative Spectroscopy and Radiative Transfer 2020 · Observational atmospheric measurement study · n=?

The impact of clouds on the brightness of the night sky

Cited 48 times in the scientific literature.

Level 4 - case-series / case-control

Observational environmental measurement study (by design analogy, not clinical CEBM)

OpenAlex W3011582680 · doi:10.1016/j.jqsrt.2020.106962 · record verified 2026-08-27

What was done

The authors analyzed the impact of cloud cover, cloud genera, and cloud base altitude on night sky brightness across locations with varying degrees of baseline light pollution. Continuous all-night sky brightness measurements were combined with meteorological data and cloud genera assessments, including a method to infer certain cloud genera directly from sky brightness patterns when observational cloud data were unavailable.

What was found

The abstract reports qualitative relationships without specific numerical values. A linear correlation was observed between cloudiness and night sky brightness, allowing categorization into three distinct light-pollution area types. Among nine identified cloud genera, Altocumulus, Cirrocumulus, and Cumulonimbus were primarily responsible for this correlation. Night sky brightness did not depend on cloud albedo. Under overcast skies, brightness was inversely related to cloud altitude, with lowest-altitude cloud genera contributing the most scattered light. Additionally, at freezing temperatures, an aerosol layer formed below Nimbostratus or Stratus clouds that thickened as temperature dropped, adding further artificial light scattering.

Why it matters

The study characterizes how specific meteorological conditions and cloud types amplify artificial light pollution at ground level. This provides an observational basis for modeling nighttime sky brightness and urban light scattering under different atmospheric conditions.

Limits

The abstract does not disclose sample sizes, the number or geographic distribution of measurement stations, observation duration, or statistical metrics (such as correlation coefficients or confidence intervals). Findings may be specific to the regional climates and lighting conditions measured.

Cited by