benny019/evaluation-of-the-Little-Dry-Season-variability-in-lagos-nigeria-2004-2023.

This research analyzes the temporal variability of key Little Dry Season(LDS) characteristics in Lagos from 2004 to 2023 using the 5-Day Cumulative Percentage Mean Rainfall method. # Analysis-of-the-Little-Dry-Season-Variability-in-Lagos-Nigeria from 2004 to 2023. ## Introduction This research, conducted as part of my industrial training in Meteorology and Climate Science, analyzes the Little Dry Season (LDS) in Lagos, Nigeria. Motivated by a prolonged dry period observed during my internship (July-November), I investigated the temporal variability of the LDS over 20 years (2004-2023) using available rainfall data. ## Skills Demonstrated This project showcased a blend of data analysis and meteorological expertise, reflecting the interdisciplinary nature of my studies. I extracted and processed ERA5 rainfall data from the Climate in Africa website, deriving key metrics like 5-day mean and cumulative rainfall. Time series and statistical analyses revealed trends and variability in LDS characteristics. Visualizations, including a tree map and cumulative rainfall line graphs and bar charts communicated more insights. My meteorological background informed the interpretation of LDS characteristics. Technically, I used Excel, SQL, and Tableau. ## Overview The Little Dry Season (LDS) is a climatological phenomenon in West Africa characterized by reduction in the amount and intensity of rainfall halfway into the wet season. It usually manifests between July and September. ## Problem Statement (Research Aims & Objectives) This project aimed to analyze the temporal variability of key LDS characteristics in Lagos using the 5-day Cumulative Percentage Mean Rainfall method. Objectives included: • Determining LDS onset and retreat dates. • Analyzing interannual variability in LDS length, rainfall, rain days, and intensity. • Identifying trends and relationships between characteristics. • Identifying extreme values and their occurrence years. ## Data Sourcing This study used daily rainfall data from the Copernicus ERA5 Reanalysis dataset, accessed via the Climate In Africa website. ERA5 is a high-resolution global atmospheric reanalysis produced by the …