Data and scripts for "Simulating AMOC tipping driven by internal climate variability with a rare event algorithm."

This dataset contains supplementary material for the paper Simulating AMOC tipping driven by internal climate variability with a rare event algorithm." (M.Cini, G. Zappa, F. Ragone, S. Corti, 2023) submitted to npj Climate and Atmospheric Science.  Preprint is available at https://www.researchsquare.com/article/rs-3215995/latest.Here we uploaded most relevant data and scripts concerning this study. Feel free to contact us for other resources.This datasets contains:
1) The output of one 125-years ensemble simulation performed with the Algorithm.
2) Time series of the AMOC index for all the simulations performed.3) All data-analysis related scripts. These scripts have been used to plot all the figures in the paper.
The script for the rare event algorithm is already available in the Supplementary material for "Rare event algorithm study of extreme warm summers and heatwaves over Europe" zenodo repository, available at https://zenodo.org/records/4763283.Simulation Architecture and model setup
All the simulations have been performed with an intermediate complexity coupled climate model, composed by the Planet Simulator (PlaSim) and the Large Scale Geostrophic Ocean (LSG). All simulations are performed at stationary greenhouse gases forcing. More information about model setup and scope of the simulations can be found in the paper.We performed 10 100-member ensemble simulations. First 125 years of the simulation are performed with the algorithm on (k=3). Then, simulations have been restarted at year 120 with the algorithm off (k=0) up to year 400. This last 380 years of simulation have been performed with only 20 members.y2480_k3_ntraj100
y2480_k3_ntraj100.tar.gz contains the output of one ensemble simulation (y2480, i.e. the one that starts at year 2480 of the control run simulation) performed with the algorithm, i.e. contains data of 125 years simulation of 100 members.Data is organized in blocks for each years. Every block contains the 4 NetCDF light file for each member and 4 files with full-size output that represent the mean state as the average of the 100 members. The 4 different file name accounts for the 4 different module output of the model: "data" for the atmosphere, "ice" for sea ice, "ocean" for the slab ocean layer in PlaSIM, lsg for LSG dynamical ocean.

Time Series
Time series of the AMOC index are contained in 10 files representing the 10 different simulations performed. In each file are present 125 .txt files, one for each year of the simulation with the algorithm on, with the annual average AMOC indices of the 100 members, and 380 .txt files, one for each year of the simulation with the algorithm off, with the annual average AMOC indices of the 20 members.

Response Analysis REA
Response Analysis REA contains the script that generates Fig.2, Fig. S3, Fig. S5, Fig. S6 and Fig. S7 of the paper. In general it provides tools for data analysis of the climate response to an AMOC slowdown.  Be aware that data of the lsg module needs different processing. 

AMOC Evolution REA
AMOC Evolution REA contains the script that generates Fig.1, Fig. 4, Fig. 5, Fig. 6 and Fig. S2 of the paper. In general it provides tools for analysis of time series and scatter plots of the AMOC evolution.  
Causes REA
Causes REA  contains the script that generates Fig.3, Fig. S4 of the paper. . In general it provides tools for analysis of driving elements of the AMOC decline. More information about these methods can be found in the "Triggering mechanisms" section of the paper.  Be aware that data of the lsg module needs different processing.