Fingerprinting the oceans: A probabilistic assessment of 20th century sea-level

Carling Hay will join us in March to discuss her recent work using probabilistic assessments to better estimate 20th century sea-level.*

Recent estimates of 20th century global mean sea-level rise are in the range 1.6-1.9 mm/yr. However, these estimates use a temporally and spatially sparse network of observations that may result in a biased estimate due to the incomplete sampling of a global field. In this talk I will present a multi-model Kalman smoother (KS) technique that addresses the above challenges. The techniques naturally accommodate spatio-temporal changes in the availability of observations and use models of the underlying physical processes responsible for sea-level change to exploit both the spatial and temporal information within the observations of the sparsely-sampled global field. Our results provide new estimates of the spatial and temporal variability in global mean sea level since 1900.

*Please note that this work doesn't use Stan, but as we discussed previously, we are expanding to be open to Bayesian approaches, agnostic on the language or exact implementation.