Problem Statement

Traditional Climate Data Collection and Forecasting Needs To Be Improved

Traditional weather forecasting systems provide generalized predictions applicable to broad regions. They do not account for localized factors such as variations in terrain, urban heat islands, or localized bodies of water, which can significantly influence weather conditions.

Moreover:

• Climate change is leading to more frequent and severe weather events, heightening the need for precise, real-time weather data.

• Accurate data is essential for predicting and mitigating the impacts of these extreme weather events on various sectors and communities.

Climate Data Sharing

Climate data often exists in silos, making it difficult for businesses, researchers, policymakers, and the public to access and use effectively. This fragmentation arises from the fact that data is gathered by numerous organizations across different regions and countries, each using varied methodologies and formats. This diversity leads to inconsistencies and a lack of standardization, complicating efforts to integrate and compare datasets. Additionally, access restrictions and proprietary data policies can further hinder the sharing of information between entities. The result is a dispersed and isolated set of data repositories, which challenges efficient climate research and decision-making processes.