Advancing Thermospheric Forecasting: A Neutral Density Enhancement Monitoring and Alert Service

Ensemble has developed foundational architecture for a proof-of-concept Neutral Density Monitoring and Alert Service. This tool uses the model output of the Whole Atmosphere Model-Ionosphere Plasmasphere Electrodynamics (WAM-IPE) Forecast System, developed by NOAA and made available by the Space Weather Prediction Center (SWPC). We process the output data of WAM-IPE to generate density profiles across Low Earth Orbit (LEO) altitudes and local atmospheric drag profiles based on a satellite’s two-line element. The effort improves Research-to-Operations-to-Research (R2OR2) capabilities by providing a cloud-based framework with which to validate the latest forecasting capabilities of space weather models against measured satellite values.

Our data pipeline functionalizes, analyzes, and stores WAM-IPE nowcasting and forecasting output at specific times and altitudes within LEO, and in post-processing computes global average density profiles and other metrics relevant for satellite operators and space weather scientists. We then propagate an orbit's satellite trajectory using predicted local neutral density values, laying the groundwork to conduct energy-based drag calculations and estimate a spacecraft’s daily altitude loss. Our flythrough tool allows for users to interact with the WAM-IPE model, visualize forecasts, and customize alerts according to their preferences; the need for such technology is well-documented through customer discovery. The platform and its associated metrics are delivered via API at a resolution in line with a satellite’s trajectory. Continued development of this Satellite Drag Explorer has necessitated a validation effort, with positive conclusion; the results of this benchmarking are presented in this talk.

Our data pipeline is made possible by the Kamodo Analysis Suite, developed in partnership with the NASA Community Coordinated Modeling Center (CCMC), which facilitates tasks such as four-dimensional interpolation, automated unit conversions, and streamlined coordinate transformations. Additionally, Ensemble has partnered with CU Boulder’s SWx-TREC, who offer model validation support.