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LMR turbo

Project description

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LMR Turbo (LMRt)

LMR Turbo (LMRt) is a lightweight, packaged version of the Last Millennium Reanalysia (LMR) framework, inspired by LMR_lite.py originated by Professor Hakim. LMRt aims to provide following extra features:

  • a package that is easy to install and import in scripts or Jupyter notebooks

  • modularized workflows at different levels:

    • the low-level workflow focuses on the flexibility and customizability

    • the high-level workflow focuses on the convenience of repeating Monte-Carlo iterations

    • the top-level workflow focuses on the convenience of reproducing an experiment purely based on a given configuration YAML file

  • convenient visualization functionalities for diagnosis and validations (leveraging the Series and EnsembleSeries of the Pyleoclim UI)

A preview of the results

Mean temperature

Mean temperature

Niño 3.4 index

Niño 3.4

Documentation

References of the LMR framework

  • Hakim, G. J., J. Emile‐Geay, E. J. Steig, D. Noone, D. M. Anderson, R. Tardif, N. Steiger, and W. A. Perkins, 2016: The last millennium climate reanalysis project: Framework and first results. Journal of Geophysical Research: Atmospheres, 121, 6745–6764, https://doi.org/10.1002/2016JD024751.

  • Tardif, R., Hakim, G. J., Perkins, W. A., Horlick, K. A., Erb, M. P., Emile-Geay, J., et al. (2019). Last Millennium Reanalysis with an expanded proxy database and seasonal proxy modeling. Climate of the Past, 15(4), 1251–1273. https://doi.org/10.5194/cp-15-1251-2019

Published studies using LMRt

  • Zhu, F., Emile‐Geay, J., Hakim, G. J., King, J., & Anchukaitis, K. J. (2020). Resolving the Differences in the Simulated and Reconstructed Temperature Response to Volcanism. Geophysical Research Letters, 47(8), e2019GL086908. https://doi.org/10.1029/2019GL086908

  • Zhu, F., Emile-Geay, J., Anchukaitis, K., Hakim, G., Wittenberg, A., Morales, M., & King, J. (2021). Volcanoes and ENSO: a re-appraisal with the Last Millennium Reanalysis. https://doi.org/10.21203/rs.3.rs-130239/v1

How to cite

If you find this package useful, please cite it with DOI: 10.5281/zenodo.2655097

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