Speaker
Description
Since the first detection of an exoplanet in 1995, the field has undergone a huge transformation, shifting the focus from planetary detection to detailed atmospheric characterisation. Ground- and space-based observatories have revealed a stunning diversity in planetary masses, radii, and orbital architectures, and exoplanetary atmospheres now hold the key to understanding the origin of this diversity through their observable spectral signatures. As the field transitions from an era of molecular "species discovery" to one of "atmospheric characterization," the synergy between space-based Low-Resolution Spectroscopy (LRS) and ground-based High-Resolution Spectroscopy (HRS) has emerged as a crucial multi-technique approach. LRS, provided by facilities like HST and JWST, offers broad wavelength coverage and sensitivity to continuum levels, enabling the detection of molecular bands. However, it remains limited in its ability to resolve individual line profiles or disentangle overlapping species. In contrast, HRS instruments (such as HARPS-N, GIANO-B, CRIRES+, ESPRESSO, and MAROON-X) resolve line shapes. This enables cross-correlation mapping of atmospheric species and probes layers above high-altitude clouds and hazes, which often mute spectral features in LRS data. By integrating these complementary datasets within joint retrieval frameworks, we can simultaneously break degeneracies between temperature structure, cloud deck pressure, and chemical abundances, constraints that are often unachievable by either technique in isolation. In this contribution, we present ongoing efforts to combine HRS and LRS observations, demonstrating how joint retrieval algorithms yield significantly tighter constraints on atmospheric composition and thermal structure compared to separate analyses. Looking ahead, the combination of the Extremely Large Telescope (ELT), ARIEL, and JWST represents the next frontier of this synergistic approach.