HAO Colloquium - Tony Mannucci, Jet Propulsion Laboratory

Medium-Range Thermosphere Ionosphere Storm Forecasts and the Space Weather Forecast Testbed

Forecasting natural phenomena is a way that scientific understanding can bring societal benefits. However, the link between scientific knowledge and predictability of natural phenomena is not a straightforward one. As part of the NASA/NSF Partnership For Collaborative Space Weather Modeling, we are emphasizing methods of improving predictive skill in the thermosphere-ionosphere (T-I) for medium-range forecasts, defined as forecasts initiated after a driving solar event such as a coronal mass ejection (CME) has been detected. For such forecasts with lead times of 1-4 days, our approach is meant to provide quantitative measures of forecast skill despite varying degrees of scientific understanding, and despite environmental factors that are often poorly constrained. Using community models of the coupled thermosphere-ionosphere system as a basis, we are developing forecasting tools that help understand the factors limiting predictability in different situations. We will describe our algorithms for “forecast variables” (FVs) that are quantities derived from model outputs and observations. FVs are designed to provide insight into what limits predictive skill under geomagnetic storm conditions. We will describe a tool we have developed, the Space Weather Forecast Testbed (SWFT), which enables users to explore relationships between upper atmospheric characteristics and geospace and solar wind variables. SWFT contains more than 10 years of ionospheric observations in the form of Global Ionosphere Maps (GIM) produced daily over that past 20 years by JPL. SWFT also contains a database of post-processed solar parameters such as solar wind velocity, ion density, temperature, magnetic field, the F10.7 and sunspot indices and geomagnetic indices. The algorithms in SWFT permit users to develop statistical forecasts using techniques adapted from machine learning, or "big data" approaches. SWFT prepares us for a transition to upper atmosphere forecasting using first-principles models, using solar wind forecasts as the basis for upper atmosphere forecasts. SWFT is currently being transitioned to the NASA/NSF Community Coordinated Modeling Center for community use.


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Thursday, October 19, 2017 - 1:30am to 2:30am

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