Utilizing a Navy Satellite Data Processing System to Display Predictions of Dangerous Fire Weather Conditions

We demonstrate the Navy’s Geolocated Information Processing System (GeoIPS®) as a systematic framework for integrating multiple satellite-based data inputs that aid in the monitoring of dangerous fire weather conditions, such as pyrocumulonimbus (pyroCb) development. Visualizing multi-source datasets often requires significant developmental overhead. GeoIPS® refines this practice, featuring a simple-to-use open-source Python code base, which in this instance combines algorithms for pyroCb prediction and detection with multiple sources of satellite data. The pyroCb prediction product uses thermodynamic profiles from the NOAA Unique Combined Atmospheric Processing System (NUCAPS) as inputs to a machine learning algorithm that provides probabilistic guidance for pyroCb development over fires detected by satellite. These NUCAPS profiles, along with GOES ABI L1b radiance and L2 fire product data, are ingested and processed by GeoIPS®, whose modular structure allows for the creation of customized plugins, such as the demonstrated pyroCb prediction tool, and streamlines the combination of these disparate data sources into one product, reducing the software development overhead needed to produce new types of combined imagery. The combination of multiple data sources and multiple pyroCb algorithms is used to illustrate the relative ease of utilizing GeoIPS® to produce new products that provide valuable insight to fire weather applications.