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DeepMIP-Eocene-p1: multi-model dataset and interactive web application for Eocene climate research

  • Sebastian Steinig
  • , Ayako Abe-Ouchi
  • , Agatha M. de Boer
  • , Wing Le Chan
  • , Yannick Donnadieu
  • , David K. Hutchinson
  • , Gregor Knorr
  • , Jean Baptiste Ladant
  • , Polina Morozova
  • , Igor Niezgodzki
  • , Christopher J. Poulsen
  • , Evgeny M. Volodin
  • , Zhongshi Zhang
  • , Jiang Zhu
  • , David Evans
  • , Gordon N. Inglis
  • , A. Nele Meckler
  • , Daniel J. Lunt
  • University of Bristol
  • The University of Tokyo
  • Stockholm University
  • Centre Européen de Recherche et d’Enseignement des Géosciences de l’Environnement (CEREGE)
  • University of New South Wales
  • Alfred Wegener Institute - Helmholtz Centre for Polar and Marine Research
  • Université Versailles St-Quentin
  • Russian Academy of Sciences
  • Biogeosystem Modelling Group
  • University of Oregon
  • Bjerknes Centre for Climate Research
  • China University of Geosciences, Wuhan
  • National Center for Atmospheric Research
  • University of Southampton
  • University of Bergen

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Paleoclimate model simulations provide reference data to help interpret the geological record and offer a unique opportunity to evaluate the performance of current models under diverse boundary conditions. Here, we present a dataset of 35 climate model simulations of the warm early Eocene Climatic Optimum (EECO; ~ 50 million years ago) and corresponding preindustrial reference experiments. To streamline the use of the data, we apply standardised naming conventions and quality checks across eight modelling groups that have carried out coordinated simulations as part of the Deep-Time Model Intercomparison Project (DeepMIP). Gridded model fields can be downloaded from an online repository or accessed through a new web application that provides interactive data exploration. Local model data can be extracted in CSV format or visualised online for streamlined model-data comparisons. Additionally, processing and visualisation code templates may serve as a starting point for advanced analysis. The dataset and online platform aim to simplify accessing and handling complex data, prevent common processing issues, and facilitate the sharing of climate model data across disciplines.

Original languageEnglish
Article number970
JournalScientific data
Volume11
Issue number1
DOIs
StatePublished - Dec 2024

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