USING A GLOBAL MODEL TO PREDICT THE HIGH LATITUDES

MCKINNELL, L.A., E.O. OYEYEMI, AND 4M. MOSERT

Bremen, Germany

Otro; XXVIII Asamblea Cientifica COSPAR 2010; 2010

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. Previous papers have shown that this new model would be a suitable replacement for the URSI and CCIR maps currently used within the International Reference Ionosphere (IRI) model for the purpose of F2 peak electron density predictions. Measured ground based ionosonde data, from 135 global stations, spanning the period 1995 to 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 as well as from individual requests) have been used for training a NN to predict the peak electron density. This paper will demonstrate the capability of this global foF2 model to predict foF2 at high latitude locations using previously unseen foF2 data from the Argentinian Antarctic stations. The model has been tested at solar minimum at the Antarctic locations since this was dictated by the availability of data from these stations. Additional high latitude data is used to demonstrate the ability of the model to perform at other solar activity levels. A comparative analysis is presented with details on areas of concern and possibilities for future improvement.