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

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 Earth's 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.

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Document Details

Document Type
Technical Report
Publication Date
Apr 26, 2016
Accession Number
AD1008324

Entities

People

  • Aaron J Ridley

Organizations

  • Board of Regents of the University of Michigan

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Artificial Satellites
  • Atmosphere Models
  • Atmospheres
  • Distribution Functions
  • Electronic Mail
  • High Latitudes
  • Magnetic Fields
  • Magnetic Storms
  • Magnetosphere
  • Models
  • Probability
  • Probability Distribution Functions
  • Probability Distributions
  • Space Weather
  • Thermosphere
  • Wind Velocity

Fields of Study

  • Environmental science

Readers

  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Space/Atmospheric Physics.

Technology Areas

  • Space