Statistics – Methodology
Scientific paper
Dec 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agufmsa11a..07d&link_type=abstract
American Geophysical Union, Fall Meeting 2006, abstract #SA11A-07
Statistics
Methodology
0520 Data Analysis: Algorithms And Implementation, 3205 Fourier Analysis (3255), 3315 Data Assimilation, 3369 Thermospheric Dynamics (0358)
Scientific paper
The upper atmospheric neutral wind patterns are a complex constantly evolving field varying over day of the year, latitude, longitude, local time, solar activity, and geomagnetic conditions. No single instrument has ever provided a truly complete global picture of thermospheric neutral winds as a function of these parameters. There are currently no reliable operational sensors or assimilation systems that can accurately provide an ongoing time series of global snap shots. This lack of routine wind data limits understanding of the ionosphere and thermosphere system because wind is a major driver and coupling mechanism. Until routine operational multi-instrument monitoring of thermospheric neutral winds becomes a reality, ionospheric and space-weather models and assimilation systems must rely on statistical analyses and empirical models. The utility of an empirical model is that it provides a comprehensive spatiotemporal view and interpolation of all available historical information and measurements. The Horizontal Wind Model (HWM-93) (Hedin et al., 1996) represents the main features of the global thermospheric general circulation patterns including seasonal changes, diurnal and semidiurnal tidal variations, the seasonal changes thereof, altitude variation, geomagnetic storm time effects, and solar cycle influences. An effort is underway to upgrade the HWM-93 wind model to the 21st century to support the NASA Living with a Star (LWS) research program. An overview of recent satellite- and ground-based data sets being utilized to upgrade the model will be presented. In addition, significant improvements to the empirical formulation and parameter estimation methodology will be discussed. Lastly results from a new prototype version of the model, HWM-07 will be presented.
Crowley Geoff
Drob Douglas P.
Emmert John
Picone Michael
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