DOI: 10.5281/zenodo.14726514
title: Causal pathway from AMOC to Southern Amazon rainforest time series data

description: Data supporting the research paper "Causal pathway from AMOC to Southern Amazon rainforest indicates stabilising interaction between two climate tipping elements"

 

The precipitation, wind, and SST-based indices are constructed from ERA5 reanalysis data (Hersbach et al 2020), provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The AR vegetation index is derived from the Global Inventory Modeling and Mapping Studies-3rd Generation V1.2 (GIMMS-3G+) satellite dataset (Pinzon et al 2023) that  provides NDVI data in bi-weekly resolution. For sensitivity tests, we also construct the AMOC index using COBE-SST2  (Hirahara et al 2014), HadCRUT5 (Morice et al 2021), HadSST4 (Kennedy et al 2019), and NOAA ERSSTv5 (Huang et al 2017) SST data. For an additional precipitation index, we use data from the Global Precipitation Climatology Centre (GPCC) by the Deutscher Wetterdienst (DWD). This is an in-situ reanalysis dataset of global land-surface precipitation from 1981–2020, based on rain gauge data from about 86,000 stations world-wide (Schneider et al 2022). The South Atlantic Anticyclone (SAA) indices are taken already aggregated from Gilliand & Keim 2018, the North Atlantic Oscillation (NAO) index is taken already aggregated from Dool et al. 2000.

 

raw data sources:

Dool H M van den, Saha S and Johansson Å 2000 Empirical Orthogonal Teleconnections J. Clim. 13 1421–35

Gilliland J M and Keim B D 2018 Position of the South Atlantic Anticyclone and Its Impact on Surface Conditions across Brazil J. Appl. Meteorol. Climatol. 57 535–53

Hersbach H, Bell B, Berrisford P, Hirahara S, Horányi A, Muñoz-Sabater J, Nicolas J, Peubey C, Radu R, Schepers D, Simmons A, Soci C, Abdalla S, Abellan X, Balsamo G, Bechtold P, Biavati G, Bidlot J, Bonavita M, De Chiara G, Dahlgren P, Dee D, Diamantakis M, Dragani R, Flemming J, Forbes R, Fuentes M, Geer A, Haimberger L, Healy S, Hogan R J, Hólm E, Janisková M, Keeley S, Laloyaux P, Lopez P, Lupu C, Radnoti G, de Rosnay P, Rozum I, Vamborg F, Villaume S and Thépaut J-N 2020 The ERA5 global reanalysis Q. J. R. Meteorol. Soc. 146 1999–2049

Hirahara S, Ishii M and Fukuda Y 2014 Centennial-Scale Sea Surface Temperature Analysis and Its Uncertainty J. Clim. 27 57–75

Huang B, Thorne P W, Banzon V F, Boyer T, Chepurin G, Lawrimore J H, Menne M J, Smith T M, Vose R S and Zhang H-M 2017 Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons J. Clim. 30 8179–205

Kennedy J J, Rayner N A, Atkinson C P and Killick R E 2019 An Ensemble Data Set of Sea Surface Temperature Change From 1850: The Met Office Hadley Centre HadSST.4.0.0.0 Data Set J. Geophys. Res. Atmospheres 124 7719–63

Morice C P, Kennedy J J, Rayner N A, Winn J P, Hogan E, Killick R E, Dunn R J H, Osborn T J, Jones P D and Simpson I R 2021 An Updated Assessment of Near-Surface Temperature Change From 1850: The HadCRUT5 Data Set J. Geophys. Res. Atmospheres 126 e2019JD032361

Pinzon J E, Pak E W, Tucker C J, Bhatt U S, Frost G V and Macander M J 2023 Global Vegetation Greenness (NDVI) from AVHRR GIMMS-3G+, 1981-2022

Schneider U, Hänsel S, Finger P, Rustemeier E and Ziese M 2022 GPCC Full Data Monthly Product Version 2022 at 2.5°: Monthly Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historical Data