Mapping the Surface of Partially Cloudy Exoplanets is Hard

In this work, we tackle the issue of inferring the albedo surface map of terrestrial exoplanets, directly from their reflected lightcurve. This is a challenging task, as this problem is degenerated, in the sense that multiple maps can yield indistinguishable lightcurves.

Moreover, planetary atmosphere are expected to host clouds, changing with time and location, aggravating the complexity of the problem. In this work, we use observations spanning multiple days to try to recover a cloud-free surface albedo map.

We demonstrate this technique as part of a Bayesian retrieval by simultaneously fitting for the fixed surface map of a planet and the time-variable overlying clouds. We test this approach on synthetic data and then apply it to real disc-integrated observations of the Earth.

We find that 8 days of continuous synthetic observations are sufficient to reconstruct a faithful low-resolution surface albedo map, without needing to make assumptions about cloud physics. For light curves with negligible photometric uncertainties, the minimal top-of-atmosphere albedo at a location is a good estimate of its surface albedo. When applied to observations from the Earth Polychromating Imaging Camera aboard the Deep Space Climate Observatory spacecraft, our approach removes only a small fraction of clouds.

We attribute this difficulty to the full-phase geometry of observations combined with the short correlation length for Earth clouds. For exoplanets with Earth-like climatology, it may be hard to do much better than a cloud-averaged map. We surmise that cloud removal will be most successful for exoplanets imaged near quarter phase that harbour large cloud systems.

Here is the link to the publication . Don't hesitate to contact me if you have questions, or if you want to discuss it !