Himawari Weather Satellites Accidentally Capture Venus, Aiding Study of Venusian Atmospheric Changes
2025-11-19 15:23
Source:National Astronomical Observatory of Japan
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Scientists have unexpectedly spotted Venus in the background of images taken by Japan's geostationary meteorological satellites Himawari-8 and Himawari-9. By collecting and analyzing these serendipitous observations, they successfully tracked temperature changes in Venus's atmosphere over nearly the past decade, offering a fresh perspective on Venusian weather.

Venus is shrouded in a thick carbon dioxide atmosphere topped with sulfuric acid clouds. Its weather patterns share similarities with Earth's but have been difficult to monitor continuously. Ground-based observations are severely limited, and space-based missions are often constrained by timing or wavelength coverage. Against this backdrop, an international team led by Manabu Nishiyama, in collaboration with the German Aerospace Center (DLR), University of Tokyo, and National Astronomical Observatory of Japan, conducted an in-depth study using Venus data that appeared in the background of Himawari Earth images.

Operated by the Japan Meteorological Agency, the Himawari satellites can distinguish 16 different "colors" in visible and infrared light and have a field of view slightly larger than Earth, allowing them to capture surrounding space. While examining the data, Nishiyama's team identified 437 instances where Venus appeared as a dot in the background. From these, they successfully observed long-term changes in Venusian weather, particularly variations in the thermal structure of the atmosphere. The study found the largest temperature fluctuations occur around Venusian sunrise, possibly linked to waves circulating through the planet's atmosphere.

These findings not only provide new insights into Venusian weather but also open a novel field of planetary observation using meteorological satellites. In the future, other Solar System planets may appear in the background of weather satellite images, revealing untapped potential in these unexplored datasets.

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