A Global Visual Framework for Analyzing Meteorological Patterns, Air Quality, and Environmental Vulnerabilities

Authors:

Sahnen Tabassum¹, Yashaswini Reddy², Apoorva Lakkaraju³, Dr. K. Shruthi⁴

Student, Department of Artificial Intelligence and Data Science, Methodist College of Engineering and Technology, Hyderabad, India^{1 2 3}

Associate professor, Department of Computer Science and Engineering, Methodist College of Engineering and Technology, Hyderabad, India⁴

Abstract

Climate change, extreme weather events, and accelerating environmental degradation present profound risks to public health, global infrastructure, agricultural productivity, and ecosystems. To foster data-driven climate resilience and proactive environmental policy, this study delivers a comprehensive visual analytics framework that evaluates the complex interactions between global weather and air quality. Utilizing a structured dataset comprising over 124,000 observations across more than 200 countries and

250 cities worldwide from 2024 to 2026, we investigate the multi-dimensional relationships between key near-surface meteorological elements including temperature, humidity, wind speed, precipitation, atmospheric pressure, cloud cover, the UV index and critical ambient air pollutants, namely PM_2.5, PM₁₀, O₃, NO₂, SO₂. The resulting visual dashboards successfully track long-term environmental trends and isolate geographic hotspots, demonstrating how specific meteorological conditions compound local air pollution and environmental vulnerabilities. By converting dense, large-scale climate repositories into intuitive, actionable visual evidence, this research establishes a vital decision-support system to help authorities and communities improve disaster response, mitigate public health hazards, manage drought and flood risks, and implement sustainable urban and agricultural strategies.

Keywords: Visual Analytics, Tableau, Climate Change, Air Quality Index, Environmental Policy, Meteorological Modeling.