A Unified Alabama Mesonet for Climate-, Fire-, and Weather-Related Decision-Support
Research Team Members
Objective:
This project aims to improve the accessibility and integration of valuable weather and soil data currently collected by multiple independent networks across Alabama. It brings together information from multiple different networks into one shared system. The result will be a user-friendly dashboard and open-access database that helps scientists, forecasters, and agencies make better decisions about droughts, fires, and weather events.
Approach:
This project will unify existing weather, climate, and soil moisture datasets from several Mesonets in Alabama into a single, standardized database. Raw data from each network will be preserved but mapped to a shared format with consistent variable names and units. High-frequency data will be processed into hourly and daily summaries to support multiple timescales of analysis.
The system is built using containerized tools managed within a Podman pod and includes a PostgreSQL database, a Django-based dashboard frontend, and support tools for editing and management. Curated database views and custom queries will make the data easier to explore and download. A public-facing dashboard will allow users to visualize and filter the data in real time or historically, improving access for researchers, forecasters, and resource managers across the state.
Impact:
Makes weather and soil data easier to access and use. Helps with quicker, more accurate drought and fire warnings. Supports climate research and emergency management. Gives public and agencies a single tool to explore and download real-time and past data.Abstract:
This project will combine weather, climate, and soil moisture data from several independent monitoring networks in Alabama into a unified and standardized system. Currently, each network operates on its own with different formats, variable names, and access methods, which makes it difficult to use the data collectively. By integrating these sources into a shared PostgreSQL database and making the data available through a user-friendly dashboard built with Django, this project will make environmental data easier to explore, compare, and download. The system will preserve each network’s original data structure while translating it into a common format with consistent units and names. High-frequency data will be processed into hourly and daily summaries to support different types of analysis. All components will be securely hosted in a Podman-managed container environment. This effort will help agencies like the National Weather Service and Alabama Forestry Commission make better-informed decisions about droughts, fire risk, and extreme weather events. It will also provide public access to valuable climate and soil information, laying the groundwork for improved research, forecasting, and environmental management across the state.