Physics – Space Physics
Scientific paper
Jun 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009adspr..43.1770m&link_type=abstract
Advances in Space Research, Volume 43, Issue 11, p. 1770-1775.
Physics
Space Physics
6
Scientific paper
A new neural network (NN) based global empirical model for the foF2 parameter, which represents the peak electron density has been developed using extended temporal and spatial geophysical relevant inputs. The first results from this new model were presented at the International Reference Ionosphere (IRI) 2006 workshop in Buenos Aires, Argentina, and showed that this new model would be a suitable replacement for the URSI and CCIR maps currently used within the IRI model for the purpose of F2 peak electron density predictions. Measured ground based ionosonde data, from 85 global stations, spanning the period 1995-2005 and, for a few stations from 1976 to 1986, obtained from various resources of the World Data Centre (WDC) archives (Space Physics Interactive Data Resource SPIDR, the Digital Ionogram Database, DIDBase, and IPS Radio and Space Services) have been used for training a NN. This paper will demonstrate the significance of the inputs chosen for the input space and their ability to be suitable predictors for foF2. In addition, this paper presents a progress report on the status of the global foF2 model, and the search for additional data to ingest into the model to complete the global representation of foF2.
McKinnell Lee-Anne
Oyeyemi Elijah O.
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