![Minimim
Temperature [°C]
Maximum
Temperature [°C]
Average Temperature
[°C]
Length data [N] 19723 19723 19723
Missing data [%] 0 0 0
Min [°C] 16.2 24.7 21.3
Max [°C] 38 47.3 41.5
Median [°C] 26 33.2 29.55
Mean [°C] 26.24 34.61 30.42
St.Dev[°C] 3.85 5.07 4.31
CV 0.15 0.15 0.14
Q (5%)[°C] 20.4 28.6 24.8
Q (25%)[°C] 23.1 30.5 26.75
Q (75%)[°C] 29.3 37.8 33.55
Q(90%)[°C] 31.5 43.2 37.25
Q (95%)[°C] 32.5 44.2 38.05
Q (99%)[°C] 34 45.4 39.25
Etude de la Variabilité Temporelle de la Température](https://image.slidesharecdn.com/mr-260731112640-bb897740/85/Comprehensive-Study-on-Temporal-Variability-of-Temperature-and-Climate-Relations-5-320.jpg)
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Uploaded byAbdi-Basid ADAN
Comprehensive Study on Temporal Variability of Temperature and Climate Relations
Author: Abdi-Basid ADAN Contact: abdi-basid@outlook.com Context & Problem Statement: This study investigates the temporal variability of daily minimum and maximum temperatures recorded at the Djibouti Aviation Station over the period 1966–2019. A major challenge addressed is the homogeneity problem in the daily temperature series, which may result from station relocations, instrumentation changes, or other non-climatic factors. Objectives: The research has three main objectives: To detect and correct inhomogeneities in the daily temperature time series using statistical breakpoint detection methods. To characterize the seasonality and long-term trends in temperature variability. To evaluate the relationships between temperature and other climatic phenomena, including humidity and Sea Surface Temperature (SST) . Data & Methodology: The analysis relies on two main datasets provided by the U.S. National Oceanic and Atmospheric Administration (NOAA): GSOD (Global Summary of the Day) – for the Djibouti-Ambouli station (coordinates: 11.550°N, 43.133°E) and Djibouti station (11.550°N, 43.150°E). GHCN (Global Historical Climatology Network) – for additional reference and cross-validation (including the King Abdullah Bin Abdulaziz station in Saudi Arabia as a regional reference). Homogeneity testing is performed using Pettitt's test on deseasonalized series to identify change points (breakpoints) in the temperature records. Expected Outcomes & Perspectives: The study will: Provide a homogenized, reliable temperature dataset for Djibouti, Quantify the influence of large-scale drivers (SST, humidity) on local temperature extremes, Support climate monitoring and early warning systems in the region. Future perspectives include extending the analysis to other variables, improving statistical downscaling, and contributing to climate adaptation planning.
