PREP-NexT / global-drought-recovery

Quantification of global drought recovery probability based on Vine Copula

Global Drought Recovery

This repository contains the Python scripts to quantify global drought recovery probability based on a Vine-Copula framework, introduced in the paper Probabilistic Assessment of Global Drought Recovery and Its Response to Precipitation Changes.

Usage

The scripts should be executed in the following order:

1. global_drought_events.py

Loads the data and extracts characteristics of drought events.

2. find_severe_droughts.py

Identifies the most severe drought event for each grid during the past 66 years (1951-2016).

3. global_drought_recovery_probability.py

• Calculates the likelihoods of drought recovery in both historcial (1951-1983) and present (1984-2016) periods.
  
• Evaluates whether changes in recovery probability between historical and present periods are statistically significant.

4. elasticity_analysis.py

Calculates the response of drought recovery probability to precipitation changes.

5. plot.py

• Plots the global recovery probability.
  
• Plots the relative changes in recovery probability between historical and present periods at subcontinent scales.
  
• Plots the response of drought recovery probability to precipitation changes under various climate scenarios.

Citation

If you use this work, please consider citing our paper:

@article{zhang2024probabilistic,
  title={Probabilistic assessment of global drought recovery and its response to precipitation changes},
  author={Zhang, Limin and Yuan, Fei and He, Xiaogang},
  journal={Geophysical Research Letters},
  volume={51},
  number={1},
  pages={e2023GL106067},
  year={2024},
  publisher={Wiley Online Library}
}

Code License

This work is licensed under the GNU General Public License v3.0. For more details, please refer to LICENSE.txt.