Spatio-temporal variability of temperature in the Montagnes district (Western Côte d’Ivoire) from 1961 to 2020.

This study investigates the spatio-temporal dynamics of temperature in the Montagnes District, located in western Côte d’Ivoire, over the period 1961–2020. The analysis draws upon a combination of long-term meteorological observations from ORSTOM (1961–2000) and satellite-derived temperature data extending through 2020. A rigorous data preprocessing protocol was applied to correct systematic biases and address missing values, thereby ensuring the robustness and consistency of the time series.Temperature trends and structural shifts were assessed using a suite of statistical tests, including the distribution-free CUSUM method and Student’s t-test for change-point detection, as well as the non-parametric Mann-Kendall test and simple linear regression for trend analysis. Results reveal a statistically significant warming trend in annual mean temperatures, estimated at +0.0011 °C per year, corresponding to an approximate 3% increase over the study period. The spatial distribution of thermal isohyets indicates pronounced heterogeneity across the district, with a consistent north–south gradient reflecting cooler northern and warmer southern zones.The intra-annual thermal amplitude, reflected in an average difference of 2.16 °C between maximum and minimum monthly temperatures, underscores notable thermal variability. Monthly analyses reveal a well-defined seasonal cycle, with temperature peaks in March and minima during the core rainy season (June–August). Notably, the most recent decade (2011–2020) exhibits an intensification of warming, particularly during March, April, and November, where recorded temperatures consistently exceed historical baselines. These findings highlight an accelerating regional warming pattern within the Montagnes District, likely attributable to broader global climate change processes. The observed trends call for the development of locally tailored adaptation strategies, particularly in the domains of agriculture and water resource management.