Turn-key routines for the RegEM EIV Climate Reconstruction Routine

Turn-key routines for the RegEM EIV code (written in R programming language) can be found here .

This code was featured in Schmidt et al. 2011:
Schmidt, G.A., Mann, M.E., Rutherford, S.D., A comment on "A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?" by McShane and Wyner, Ann. Appl. Stat., 5, 65 70, 2011.

Mann (2004) Time Series Smoothing Routine

Provides smoothed time series and measure of misfit with option of boundary conditions useful in series with long-term trends or non-stationary behavior.

The Smoothing Routine is Described in:

Mann, M.E., On Smoothing Potentially Non-Stationary Climate Time Series, Geophysical Research Letters, 31, L07214, doi: 10.1029/2004GL019569, 2004.

Matlab Smoothing Routine Code

Updated Version yields a smoothed series based on combination of boundary constraints that minimizes MSE relative to raw time series

Updated routines from Mann (2008) can be found here.
Download a PDF of the article here.

Mann & Lees Multi-Taper Method (MTM)

  • Multitaper spectral analysis which provides an optimally low-variance, high-resolution spectral estimate.
  • Assumptions regarding signal (narrowband, but not strictly periodic) and noise ("red") that are most appropriate in the context of climate studies.
  • A "robust" method for accurate determination of the noise component of the spectrum.

The MTM Method is Described in:

Mann, M.E., Lees. J., Robust Estimation of Background Noise and Signal Detection in Climatic Time Series, Climatic Change, 33, 409-445, 1996.

The MTM Method is Used in the SSA-MTM Toolkit

MTM Fortran code

Mann & Park MTM-SVD Multivariate Signal Analysis

  • Detection of irregular spatiotemporal oscillatory signals immersed in spatially-correlated coloured noise with optimal signal detection properties
  • "Evolutive'' approach to detecting intermittent and/or frequency-modulated spatiotemporal oscillations.
  • Reconstruction of spatial and temporal patterns of oscillatory climate signals

MTM-SVD Fortran codes, synthetic test dataset, and analysis results

NOTE: an issue was brought to our attention about averaging angles in the code: mtm-svd-recon.f. More details and a potential fix can be found here.

Codes Include:
  1. "LFV" multivariate spectrum estimation
  2. Spatiotemporal signal reconstruction
  3. Bootstrap confidence level estimation procedure, along with required subroutines, makefiles, and the synthetic test input and output.

MATLAB version of the code can be found HERE. MATLAB code generously provided by Marco Correa-Ramirez and Samuel Hormazabal See their paper here

Python version of the code can be found HERE and is derived from the MATLAB code developed by Marco Correa-Ramirez and Samuel Hormazabal. Python code generously provided by Mathilde Jutras, a doctoral student at McGill University as of July 2020.

MTM-SVD References

Miscellaneous Data and Tools

Mann et al. "Proxy-Based Reconstructions of Hemispheric and Global Surface Temperature Variations over the Past Two Millennia" (Proceedings of the National Academy of Sciences, 2008)
Mann et al. "Global signatures and dynamical origins of the Little Ice Age and Medieval Climate Anomaly" (Science, 2009)
Mann et al. "Underestimation of volcanic cooling in tree-ring- based reconstructions of hemispheric temperatures" (Nature Geoscience, 2012)
Mann et al. "Robustness of proxy-based climate field reconstruction methods" (Journal of Geophysical Research, 2007)
Mann et al. "Atlantic hurricanes and climate over the Past 1500 Years" (Nature, 2009)
Kozar et al."Stratified statistical models of North Atlantic basin-wide and regional tropical cyclone counts" (JGR, 2012) Tropical Cyclone Counts (CSV file)
Mann, M.E., Lloyd, E.A., Oreskes, N., Assessing Climate Change Impacts on Extreme Weather Events: The Case For an Alternative (Bayesian) Approach, Climatic Change, 144, 131-142, 2017.