Statistical Tools for Climate Change Analysis

A comprehensive collection of statistical functions for climate change research. Provides tools for temporal trend detection based on the Mann-Kendall (MK) test (Mann 1945 ; Kendall 1975, ISBN:0852641990) and Sen's slope (Sen 1968 ), spatial autocorrelation using Moran's I (Moran 1950 ), extreme value analysis using the Generalised Extreme Value (GEV) distribution and Peaks-Over-Threshold (POT) method (Coles 2001 ), standardised drought indices including the Standardised Precipitation Index (SPI; McKee et al. 1993) and the Standardised Precipitation Evapotranspiration Index (SPEI; Vicente-Serrano et al. 2010 ), and formal detection-attribution methods via optimal fingerprint regression and Empirical Orthogonal Function (EOF) analysis (Allen and Tett 1999 ), and apparent temperature via the heat index (Steadman 1979 ). Suitable for both station-level time series and gridded climate fields.


climatestatsr

Statistical Tools for Climate Change Analysis
Author: Sadikul Islam


Overview

climatestatsr is a comprehensive R package providing statistical functions for climate change research. It covers temporal trend analysis, spatial analysis, extreme event assessment, standardised climate indices, and formal detection-attribution methods.

Installation

Install from source:

install.packages("climatestatsr_0.1.0.tar.gz",
                 repos = NULL, type = "source")

Function Families

Family Key Functions
Temporal mk_test, sens_slope, change_point_detection, seasonal_decompose_climate, rolling_trend, temporal_homogeneity, trend_significance, autocorrelation_climate
Spatial morans_i, hot_cold_spots, spatial_interpolate, spatial_trend_field, cluster_climate_zones, spatial_anomaly, elevation_lapse_rate
Extreme Events fit_gev, return_period, peaks_over_threshold, heat_wave_detection, cold_spell_detection, drought_spell, extreme_value_index
Climate Indices spi, spei, pdsi_simple, heat_index, wind_chill, frost_days, growing_degree_days, diurnal_temp_range
Attribution detection_attribution, fingerprint_analysis, optimal_fingerprint
Utilities fill_gaps_climate, homogenize_series, aggregate_climate, anomaly_baseline, standardize_climate, climate_summary

Quick Example

library(climatestatsr)

# Mann-Kendall trend test
set.seed(42)
temp   <- 14 + 0.025 * seq_len(50) + stats::rnorm(50, 0, 0.4)
result <- mk_test(temp)
print(result)

# Sen's warming rate per decade
ss <- sens_slope(y = temp)
cat("Warming:", round(ss$slope_decade, 3), "deg C per decade\n")

# SPI drought index
precip <- stats::rgamma(360, shape = 2, scale = 30)
spi3   <- spi(precip, scale = 3)

# GEV extreme value analysis
ann_max <- rgev_sim(50, mu = 35, sigma = 4, xi = 0.1)
gev     <- fit_gev(ann_max)
rp      <- return_period(gev, c(10, 50, 100))
print(rp)

Citation

citation("climatestatsr")

Islam, S. (2026). climatestatsr: Statistical Tools for Climate Change Analysis. R package version 0.1.0.

License

GPL-3. See LICENSE for details.

Contact

Sadikul Islam (ORCID: 0000-0003-2924-7122)
E-mail: [email protected]

Reference manual

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install.packages("climatestatsr")

0.1.2 by Sadikul Islam, 4 months ago


Browse source code at https://github.com/cran/climatestatsr


Authors: Sadikul Islam [aut, cre] (ORCID: , Rajesh Kaushal [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports stats, graphics, utils

Suggests ggplot2, sf, ncdf4, testthat, knitr, rmarkdown


See at CRAN