Accession Number:

AD1008324

Title:

Utilizing Probability Distribution Functions and Ensembles to Forecast lonospheric and Thermosphere Space Weather

Descriptive Note:

Technical Report,01 Jun 2012,30 Nov 2015

Corporate Author:

REGENTS OF THE UNIVERSITY OF MICHIGAN ANN ARBOR United States

Personal Author(s):

Report Date:

2016-04-26

Pagination or Media Count:

16.0

Abstract:

The upper atmosphere of the Earth is strongly driven by the solar wind and interplanetary magnetic field IMF, which are only measured about one hour before they encounter the Earths magnetosphere. This means that it is almost impossible to predict the state of the upper atmosphere without predicting the solar wind and IMF. The research grant focused on predicting the solar wind velocity for up to five days ahead of time. A new model of the solar wind velocity was created using probability distribution functions. This new model performs as well or better than other modern models of the solar wind velocity. In addition, significant research was conducted on validating our upper atmosphere model and specifying therespond to drivers.

Subject Categories:

Distribution Statement:

APPROVED FOR PUBLIC RELEASE