Climate forecasting system distributed architecture

Abstract

Climate forecasting has received considerable attention due to its critical importance for decisionmaking in areas such as agriculture, natural resource management, and disaster preparedness. In recent years, the use of distributed architectures for Internet of Things (IoT)-based climate forecasting systems has emerged as an effective approach to provide scalable and resilient solutions. This thesis provides an overview of distributed architectures as applied to climate forecasting systems and explores how these systems can improve climate forecasting skills while overcoming key challenges of scalability, heterogeneity, and data security.