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SWFT (2020)

Space Weather Forecast Testbed

Model Description

The Space Weather Forecasting Testbed is a machine learning tool that allows a user to combine a variety of observations of solar wind and geomagnetic activity indices to form a forecast model of any of the space weather-relevent parameters.

Model Figure(s) :

Model Inputs Description

Inputs include a current time, learning interval, cross-validation interval, intended lead time and the forecast type: data (continuous) or categorical (discrete values based on crossing thresholds).

Model Outputs Description

Time series of targeted index values during learning and validation intervals, scatter plot of model-data comparison and error distribution.

Model Caveats

Change Log

Model Acknowledgement/Publication Policy (if any)

Model Domains:

Space Weather Impacts:

Phenomena :

Simulation Type(s):

Temporal Dependence Possible? (whether the code results depend on physical time?)

Model is available at?

Source code of the model is publicly available?

CCMC Model Status (e.g. onboarding, use in production, retired, only hosting output, only source is available):

Code Language:

Regions (this is automatically mapped based on model domain):

Contacts :

Acknowledgement/Institution :

Relevant Links :

Publications :

Model Access Information :

Linked to Other Spase Resource(s) (example: another SimulationModel) :

Curator: Chiu Wiegand | NASA Official: Dr. Masha Kuznetsova | Privacy and Security Notices | Accessibility | CCMC Data Collection Consent Agreement