Preshantha Climate Change Adaptation Data
Description
This Excel File contains Interview surveys and climate data related to climate change adaptation in rural areas within the eThekwini Municipality, KwaZulu-Natal Province, South Africa.
Files
Steps to reproduce
Climate Data processing and Analysis The quantitative method used in this study follows Naicker and Njoya (2025), drawing on daily temperature and rainfall data from 1970–2023 obtained from the South African Weather Service (SAWS) and the South African Sugar Research Institute (SASRI). Records from multiple weather stations across northern and southern Durban, Mount Edgecombe, Durban South, Louis Botha, Merebank, Wentworth, and Athlone Park, were included to capture spatial climate variation within the eThekwini Municipality. Before analysis, the same approach adopted in Naicker and Njoya (2025) was used to process the climate data for accuracy and completeness. Missing or incomplete entries were supplemented using nearby stations with continuous, comparable records to maintain temporal consistency over the 53 years. To minimise short-term fluctuations, daily data were aggregated into monthly and then annual mean temperature and rainfall values. The dataset was standardised by aligning date formats, units, and variables across stations, ensuring seamless integration. This rigorous verification, cleaning, and structuring process produced a reliable dataset for assessing long-term climatic trends within the municipality. To establish baseline climate conditions for this study, mean annual maximum temperature, minimum temperature, and rainfall were averaged in Microsoft Excel over the WMO-recommended 1991–2020 period. These baseline values were then applied to the full dataset (1970–2023) to calculate long-term anomalies and trends relative to recent climate conditions using the anomaly formula. Long-term climate trends, mean annual temperature and rainfall anomaly datasets were ploted in R software. Interview analysis Qualitative data for this study were collected through semi-structured interviews and a focus group workshop, guided by a mixed-method questionnaire containing both closed- and open-ended questions. The qualitative data were analysed using NVivo to organise transcripts and code responses into themes, enabling the identification of patterns and insights into CBA. This thematic analysis facilitated a systematic comparison across stakeholder groups and deepened the understanding of community responses to climate challenges.
Institutions
- University of KwaZulu-Natal - Westville Campus