Work

A Gaussian process state-space model for atmospheric CO2 and sea surface temperature index reconstruction from boron isotope and planktonic δ18O proxies

Year: 2020

Type: conference-paper

Abstract: It often occurs in practice that only a small number of observations are given for reconstructing past climate events in the field of paleoclimatology. State-space models can overcome such scarcity by giving priors to those hidden states to make them correlated to one another. Inferring multiple events simultaneously from various proxies to exploit their mutual dependency is another option. Here we present a Gaussian process state-space model to reconstruct both atmospheric CO2 and sea surface temperature index from boron isotope and planktonic δ18O proxies.

Source: International Workshop Climate Informatics

DOI: 10.1145/3429309.3429316

Authors: Taehee Lee, Charles E. Lawrence

Institutions: Harvard University, Brown University

Language: English

Topic: Geology and Paleoclimatology Research

Subfield: Atmospheric Science

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDG: Climate action

Open Access status: bronze

Funders: National Science Foundation, Brown University