I was reading that a planet sized moon orbiting a gas giant while still within the star’s habitable zone, would experience a pretty funky and awesome day/ night cycle with the light bouncing off the gas giant from the host star, illuminating the night side face of the moon. The mid day planetary eclipse dropping part of the moon into relative darkness just as quickly!

I’d love to see what this may look like! I’m not sure if such a visualization exists and if one doesn’t, I highly support someone making one!

Best wishes :)

See also: The publication in ArXiV

What can one learn by observing the light curve of an exoplanet? Especially in several spectral bands. Here is some research on that, using the Earth as an example.

• Using Deep Space Climate Observatory Measurements to Study the Earth as an Exoplanet - IOPscience
• Earth as a Proxy Exoplanet: Deconstructing and Reconstructing Spectrophotometric Light Curves - IOPscience
• Earth as an Exoplanet: A Two-dimensional Alien Map - IOPscience
• Earth as a Proxy Exoplanet: Simulating DSCOVR/EPIC Observations Using the Earth Spectrum Simulator - IOPscience
• Deep Space Climate Observatory - Wikipedia - DSCOVR

The DSCOVR satellite observes the Earth from Earth-Sun L1, about 1.5 million kilometers (gigameters) toward the Sun. It can take pictures in several wavelength bands, not just RGB, at wavelengths 317.5, 325, 340, 388, 443, 551, 680, 688, 764, and 779.5 nanometers: the visible range with some nearby ultraviolet and infrared. For simulated observations as an exoplanet, one integrates over the surface of the Earth.

The papers show pictures of the Earth in these different wavelengths. By comparing those pictures, one can recognize different kinds of features.

The first paper calculates for infrequent observations the likelihood of finding our planet's rotation rate. It's close to 1 for more frequent than 3 times a day, and declines to a small amount for one observation each 1.5 days.

The second paper finds the typical spectra of ocean, vegetation, desert, snow/ice, low clouds, and high clouds, and also does principal components analysis, a common data-mining technique, on observations. The first component is mainly for low clouds, the second component for ocean, vegetation, and desert, and the third and fourth components for high clouds. Snow/ice is like a mixture of low clouds and high clouds.

The third paper has a reconstructed surface map, though I could not follow how one gets from one dimension to two dimensions.

The fourth paper discusses an Earth Spectrum Simulator.

This kind of work should be extended to other Solar System celestial bodies, since we now have a good idea of the surfaces of most of the larger ones.

Simulations of Light Curves from Earth-like Exoplanets - Planetary Habitability Laboratory @ UPR Arecibo at the Internet Archive. I could not find any published version, but I verified the results with my own calculations. The simulations were done with RGB color bands, the most readily available sort of multiple wavelength bands.

The Earth is usually bluish, but when the Sahara Desert is well-illuminated and in good view, the Earth's color is neutral. So one can see that feature across interstellar space. Or more properly, a super Sahara, with that desert, the Arabian Desert, and to some extent, deserts in Iran and Central Asia.

Looking at other planetary-mass objects (planemos) or geophysical planets, the clouded-over ones - Venus, Jupiter, Saturn, Uranus, Neptune, and Titan - have little or no noticeable variation. Jupiter's Great Red Spot and Neptune's Great Dark Spot barely show up.

The solid-surface ones vary from Mercury, with very little variation, to Iapetus, with very strong variation. In between are Mars, the Moon, and the Earth.

This is my interpretation of the data available for this system's planets. The planet's sizes are to scale. I took inspiration from the already exisiting artistic visualizations and created my own in Blender. Happy to hear your thoughts!