Published July 5, 2023 | Version v1
Dataset Open

Climate Time Series: precipitation, SST, ONI and random time series

Authors/Creators

Description

Dataset composed of climate monthly time series ranging from 1950 to 2016.

Variables:

  • Norheastern Brazil precipitation
    • NEB_highest: region with the highest Pearson correlation with ONI and TNAtl
    • NEB_mean: average precipitation of the whole region of interest
    • NEB_lowest: region with the lowest Pearson correlation with ONI and TNAtl
  • Southern Ural Mountains region precipitation (SRUNK)
  • Oceanic Niño Index (ONI)
  • Tropical North Atlantic SST (TNAtl)
  • Gaussian Random Time Series (random_ts)
  • Prior time series processed by a Wavelet filter (except for the the random_ts)
    • wavelet_NEB_highest
    • wavelet_NEB_mean
    • wavelet_NEB_lowest
    • wavelet_SRUNK
    • wavelet_AtlN
    • wavelet_ONI

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The dataset was created and used in the following paper:

Evaluation of Time Series Causal Detection Methods on the Influence of Pacific and Atlantic Ocean over Northeastern Brazil Precipitation (pdf)(pdf)

JEC Cruz, MT Kayano, AJP Calheiros, SR Garcia, MG Quiles
International Conference on Computational Science and Its Applications (ICCSA), 2023

 

more information can be found in https://jkreuz.github.io/publications/

Files

JCruz2023_ICCSA.csv

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Additional details

Identifiers

DOI
10.1007/978-3-031-36805-9_28

Related works

Is published in
Conference proceeding: 10.1007/978-3-031-36805-9_28 (DOI)

Software

Repository URL
https://jkreuz.github.io/publications/