GEOSTORM | Devpost

API Connecting
Disaster Data View
Climate Data View
Environmental Data View

Abstract The GEOSTORM is a web platform driven by data, designed to collect and display real-time global climate indicators. The aim of this initiative is to offer accessible, evidence-based insights into climate change metrics, including temperature anomalies, carbon emissions, sea level rise, and extreme weather patterns, thereby enhancing public awareness and informing policy decisions. This document details the rationale behind the project, the methodologies employed, the technologies utilized in its development, and the challenges faced during its implementation.

Introduction Climate change is one of the most urgent global issues of the 21st century. Although there is a wealth of climate data available from various organizations, this information is frequently fragmented, complex, or not easily accessible to the general public. This project was initiated to bridge the divide between scientific data and public comprehension by creating a centralized, interactive tool that presents climate trends in a straightforward and actionable manner.

Methodology The development of the GEOSTORM adhered to a systematic process that included:

Data Acquisition: We obtained datasets from credible organizations such as NASA, NOAA, the IPCC, and the World Bank. APIs and open data repositories were employed to gather current metrics on global climate indicators. Data Processing: The gathered data was cleaned, standardized, and organized in a structured format. Aggregation and normalization processes were applied to resolve inconsistencies among various data sources. Application Development: The platform was constructed using a contemporary web stack. React.js and Tailwind CSS were utilized for the frontend, facilitating a responsive and user-friendly interface. The backend, developed with Node.js and Express, managed API integration, data transformation, and caching. Visualization libraries like Chart.js and D3.js were used to create dynamic and interactive graphs.

Deployment: The application was deployed using Vercel to guarantee rapid, scalable performance.