The NOAA Southern Regional Climate Center (SRCC) in partnership with the Southern Climate Impacts Planning Program has developed climate data-based information tools. The data-driven climate information tools rely heavily on Python for the generation and supply of climate data and spatiotemporal layers. Some of the information tools include a web-based drought tool and a set of dynamic chart-based applications. Python-based programmable interfaces to the Applied Climate Information System (ACIS) provided seamless data access and efficient web toolkits within Python helped in faster web applications.

At the SRCC, Python is also used in a high-performance computing environment for fast parallel computation of gridded climate data sets. Map-based visualization of the generated gridded data layers is facilitated by Python's support for numerical processing and statistical libraries.