The Phanerozoic Technique Averaged Surface Temperature Integrated Curve: A record of Phanerozoic global mean surface temperature using data assimilation
Abstract
Reconstructing the evolution of global mean surface temperature (GMST) across the Phanerozoic is integral to understanding the links between Earths climatic, biologic, and chemical histories, and for contextualizing and communicating anthropogenic climate change to the public. Nevertheless, quantifying global climate in deep time using a standardized method presents unique challenges. With increasing geologic age, fewer proxies are available with which to estimate paleotemperature; existing data come from a limited range of environments and latitudes, and have a higher probability of diagenetic alteration and larger uncertainties in proxy system model assumptions. Likewise appropriate boundary conditions are progressively difficult to constrain in deep time Earth system models (ESMs). These limitations, however, can largely be overcome using data assimilation, a statistical method that integrates geographically disparate proxy data with ESMs, utilizing data from myriad proxies and accounting for proxy and model uncertainty. The resulting full-field climate reconstructions permit a more robust calculation of GMST and assimilation across multiple time steps yields a reproducible curve of Earths GMST. Here, we present the first iteration of PhanTASTIC (Phanerozoic Technique Averaged Surface Temperature Integrated Curve), the first statistically rooted and internally consistent record of GMST for the Phanerozoic, and its companion sea surface temperature (SST) database. The database, which includes over 135,000 SST proxy values from the last 500+ myr, was compiled with help from members of the paleoclimate community and will be made publicly available. SST proxy data from each of the 100 Phanerozoic stages are assimilated with a suite of HadCM3 ESM simulations, run at varying greenhouse gas concentrations and paleogeographies, and GMST is calculated. We explore the sensitivity of our results to the primary assumptions underlying the approach (e.g., seawater chemistry) and constrain the full range of uncertainty by iterating through different values at each stage. We evaluate the impact of our results to the inclusion or exclusion of certain proxies, investigate the causes of incongruities at specific time intervals, and compare our findings with existing GMST curves derived by other means.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMPP24B..04J