Global models from sparse data: A robust estimate of Earth’s residual
topography spectrum
Abstract
A significant component of Earth’s surface topography is maintained by
stresses induced by underlying mantle flow. This ‘dynamic’ topography
cannot be directly observed, but it can be approximated — particularly
at longer wavelengths — from measurements of residual topography,
which are obtained by removing isostatic effects from the observed
topography. However, as these measurements are made at discrete,
unevenly-distributed locations on Earth’s surface, inferences about
global properties can be challenging. In this paper, we present and
apply a new approach to transforming point-wise measurements into a
continuous global representation. The approach, based upon the
statistical theory of Gaussian Processes, is markedly more stable than
existing approaches — especially for small datasets. We are therefore
able to infer the spatial pattern, wavelength and amplitude of residual
topography using only the highest-quality oceanic spot measurements
within the database of Hoggard et al. (2017). Our results indicate that
the associated spherical harmonic power spectrum peaks at l=2, with
power likely in the range 0.46–0.76 km^2. This decreases by over an
order of magnitude to around 0.02 km^2 at l=30. Around 85% of the
total power is concentrated in degrees 1–3. Our results therefore
confirm previous findings: Earth’s residual topography expression is
principally driven by deep mantle flow, but shallow processes are also
crucial in explaining the general form of the power spectrum. Finally,
our approach allows us to determine the locations where collection of
new data would most impact our knowledge of the spectrum.