DOI: 10.5061/dryad.xd2547dvh
title: Data and code from: A non-parametric study of temperature trends in Fiji over five decades

description: Small Island Developing States (SIDSs) like Fiji are highly vulnerable to
 climate change, yet long term, localized analyses of temperature trends
 remain limited. This study investigates annual mean minimum (Tmin ),
 maximum (Tmax), and average (Tavg) temperature trends across 23
 meteorological stations in Fiji over the period of 1970 to 2023, using the
 Mann-Kendall (MK) test, its modified variant (MMK) for accounting for
 autocorrelation, and the Sen's Slope (SS) estimator. The results
 reveal widespread and statistically significant warming, with 57 % of
 stations showing increases in minimum temperature (e.g., Vunisea: 0.33
 °C/decade; Laucala: 0.30 °C/decade) and 78 % in maximum temperature (e.g.,
 Navua: 0.61 °C/decade; Viwa: 0.55 °C/decade). A majority of the stations
 (91 %) recorded rising average temperatures, with the strongest warming
 observed in coastal and low-lying regions. Tmax exhibited the most intense
 warming at specific locations (e.g., Viwa, Yasawa, Navua), while T min
 showed more spatially consistent moderate increases across the country.
 Tavg trends fell between these two extremes, reflecting combined effects.
 The MMK test confirmed the robustness of the trends, while the SS
 estimator showed that Fiji's warming rates exceeded global and
 regional benchmarks. These findings underscore the urgency of implementing
 adaptation measures in climate-sensitive sectors, prioritizing the highest
 warming stations, and providing a critical evidence base for policy
 development and improved climate monitoring in SIDSs.
description: # Data and code from: A non-parametric study of temperature trends in Fiji
 over five decades Dataset DOI:
 [10.5061/dryad.xd2547dvh](10.5061/dryad.xd2547dvh) ## Description of the
 data and file structure This repository contains the data and code related
 to the manuscript "A non-parametric study of temperature trends in
 Fiji over five decades". ### Files and variables #### File:
 Data_and_Code.zip **Description:**\ **Data Files** 1. **tmin.csv**
 Contains daily/monthly minimum temperature data. **Missing Values**:
 Represented as`"NA"`. 2. **tmax.csv** Contains daily/monthly
 maximum temperature data. **Missing Values**: Represented
 as`"NA"`. 3. **avg.csv** Contains daily/monthly average
 temperature data. **Missing Values**: Represented as `"NA"` ####
 **Code Files** 1. **Descriptive_statistics.R** Performs summary statistics
 on the temperature datasets (mean, standard deviation, min, max). 2.
 **Trend_analysis.R** Performs time-series trend analysis on temperature
 data using Mann-Kendall test. 3. **Trend_lines.R** Produces trend line
 plots for minimum, maximum, and average temperatures across different time
 periods and stations. ## Code/software To analyze the data, the following
 free and open-source software and tools were used: * **R (version
 4.4.0)**\ *Description*: A free software environment for statistical
 computing and graphics.\ *Website*:
 [https://cran.rstudio.com/](https://cran.rstudio.com/) * **RStudio
 (version 2025.05.0)**\ *Description*: A free integrated development
 environment (IDE) for R. It provides an intuitive interface to run R
 scripts and visualize outputs.\ *Website*:
 [https://posit.co/download/rstudio-desktop/](https://posit.co/download/rstudio-desktop/) To view the data, the following software were used: * **Microsoft Excel**\ *Description*: A spreadsheet application used to open and view CSV files in tabular form. Compatible alternatives include LibreOffice Calc.\ *Version*: Microsoft Excel 2016 or later.\ *Website*: [https://www.microsoft.com/en-us/microsoft-365/excel](https://www.microsoft.com/en-us/microsoft-365/excel)