🌧️ Precipitation Indices Analysis using precintcon

This project provides a complete R workflow for computing a range of precipitation-based indices from daily rainfall data across multiple meteorological stations. The workflow is based on the precintcon R package, and includes the calculation of several standard indices used in climate variability analysis.

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📂 Project Structure

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├── clmto.csv                  # Input file: daily rainfall data in long format
├── precipitation_indices.R    # Main R script
├── pcd_result.xlsx            # Output: Precipitation Concentration Degree
├── pci_seasonal_result.xlsx   # Output: PCI Seasonal
├── pci_supraseasonal_result.xlsx # Output: PCI Supraseasonal
├── pcp_result.xlsx            # Output: Precipitation Concentration Period
├── spi_result.xlsx            # Output: Standardized Precipitation Index (3-month)
├── rai_result.xlsx            # Output: Rainfall Anomaly Index (monthly)
├── tii_result.xlsx            # Output: Temporally Irregularity Index
└── README.md                  # Project documentation

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📊 Indices Computed

1. PCD – Precipitation Concentration Degree
2. PCI (Seasonal and Supraseasonal) – Precipitation Concentration Index
3. PCP – Precipitation Concentration Period
4. SPI – Standardized Precipitation Index (3-month aggregation)
5. RAI – Rainfall Anomaly Index (monthly)
6. TII – Temporally Irregularity Index

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🧪 Requirements

• R ≥ 4.0
• Packages:
  • tidyverse
  • precintcon
  • writexl
  • readr
  • purrr
  • tibble

Install all required packages using:

install.packages(c("tidyverse", "precintcon", "writexl"))

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🧬 Data Format

Input CSV file clmto.csv must contain the following columns:

Station_Name	Year	Month	Day	RR
Station_A	1991	1	1	0
Station_A	1991	1	2	5
...	...	...	...	...

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🚀 Running the Analysis

Simply source the main script in R:

source("precipitation_indices.R")

This will generate Excel files with the computed indices for each station.

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📈 Applications

• Climatological research
• Drought analysis
• Climate variability assessment
• Early warning systems
• Agricultural planning

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📘 References

• precintcon package documentation: https://cran.r-project.org/web/packages/precintcon/
• Martinaitis, S.M. et al. (2015). Application of precipitation concentration indices in climate studies.
• WMO Guidelines on Climate Indices

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👤 Author

Adaman Yoda
National Meteorological Agency of Burkina Faso
PhD Candidate, AI for Weather Forecasting
Email: [adamouyod@gmail.com]

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📄 License

This project is open-source and available under the MIT License.