Published March 1, 2026 | Version v1
Journal article Open

Numerical Investigation of Weather Pattern Cycles and their role in Food Security under climate change

  • 1. Department of Pure and Applied Mathematics, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, Kenya.

Description

Abstract

Climate change has intensified the variability of weather patterns, posing significant threats to agricultural productivity and food security, particularly in climate-vulnerable regions. This study presents a numerical investigation of weather pattern cycles and their influence on food security under changing climatic conditions. A computational framework implemented in MATLAB is developed to simulate temperature and precipitation variability and to assess their impacts on crop yield potential and post-harvest stability. The governing continuity, momentum, energy, and moisture transport equations are solved numerically, incorporating key dimensionless parameters, namely the Rayleigh, Reynolds, Prandtl, and Lewis numbers, to characterize buoyancy-driven flow, heat transfer, and moisture diffusion under climate forcing. Historical climate data are integrated with numerical simulations to capture seasonal and inter-annual variability, while sensitivity analyses are performed to evaluate agricultural system responses to projected climate scenarios. The results indicate that increasing Rayleigh number amplifies thermal instability and moisture redistribution, whereas higher Lewis numbers suppress mass diffusion, leading to localized humidity accumulation and elevated post-harvest losses. Elevated Reynolds numbers enhance convective mixing, intensifying temperature and moisture fluctuations. Critical thresholds are identified beyond which crop productivity and storage stability deteriorate rapidly, particularly during prolonged dry spells and extreme precipitation events. The findings highlight the importance of adaptive strategies such as optimized harvest scheduling, improved ventilation, and climate-responsive storage technologies. Overall, this study provides quantitative insight into the coupled effects of climate variability and heat–mass transfer on food security and offers a modeling-based framework to support climate-resilient agricultural planning and policy development.

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Dates

Accepted
2026-02-28