Gravimetry across spatial scales – how powerful is gravity?

Gravity is a fundamental geophysical method that provides unique insight into subsurface density variations. Its sensitivity spans an exceptional range of spatial scales, from centimetre-scale laboratory experiments and borehole measurements to continental - and global-scale satellite observations. Despite its long-standing application, the practical limits and resolving power of gravimetry across these scales are still not widely appreciated. At regional to global scales, satellite missions such as GRACE and GOCE have transformed our understanding of mass redistribution within the Earth system. They enable the monitoring of ice mass loss, hydrological change, and large-scale mantle processes, achieving microgal (10⁻⁸ m s⁻²) accuracy with spatial resolutions of several hundred kilometres. These capabilities demonstrate gravimetry’s strength in detecting large-scale density anomalies and temporal mass transport. At crustal and reservoir scales, terrestrial and airborne gravity measurements resolve subtle variations related to geological structures, sedimentary basins, and fluid movements. Advanced data processing- such as terrain, Bouguer, and isostatic corrections- improves signal fidelity, while time-lapse relative gravimetry can detect changes associated with e.g. volcanic unrest, groundwater depletion, and reservoir dynamics down to the sub-microgal level. At the smallest scales, absolute gravimeters and emerging quantum sensors push precision further, enabling laboratory-based density determinations and environmental monitoring with unprecedented stability. Increasing resolution, however, introduces challenges related to topographic effects, instrumental drift, and signal ambiguity, requiring robust modelling and/or inversion strategies, and integration with complementary geophysical data. We review representative applications across satellite, regional, and local domains, quantify achievable spatial and temporal resolution, and discuss future perspectives, joint interpretation with magnetic and seismic methods, and the growing role of artificial intelligence in gravity data analysis.