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|Title:||Improving the twilight model for polar cap absorption nowcasts|
|Authors:||Rogers, N. C.|
Verronen, P. T.
Warrington, E. M.
Danskin, D. W.
|Publisher:||American Geophysical Union (AGU), Wiley|
|Citation:||Space Weather, 2016 14|
|Abstract:||During solar proton events (SPE), energetic protons ionize the polar mesosphere causing HF radio wave attenuation, more strongly on the dayside where the effective recombination coefficient, αeff, is low. Polar cap absorption models predict the 30 MHz cosmic noise absorption, A, measured by riometers, based on real-time measurements of the integrated proton flux-energy spectrum, J. However, empirical models in common use cannot account for regional and day-to-day variations in the daytime and nighttime profiles of αeff(z) or the related sensitivity parameter, m = A / sqrt(J). Large prediction errors occur during twilight when m changes rapidly, and due to errors locating the rigidity cutoff latitude. Modeling the twilight change in m as a linear or Gauss error-function transition over a range of solar-zenith angles (χl < χ < χu) provides a better fit to measurements than selecting day or night αeff profiles based on the Earth-shadow height. Optimal model parameters were determined for several polar cap riometers for large SPEs in 1998–2005. The optimal χl parameter was found to be most variable, with smaller values (as low as 60°) postsunrise compared with presunset and with positive correlation between riometers over a wide area. Day and night values of m exhibited higher correlation for closely spaced riometers. A nowcast simulation is presented in which rigidity boundary latitude and twilight model parameters are optimized by assimilating age-weighted measurements from 25 riometers. The technique reduces model bias, and root-mean-square errors are reduced by up to 30% compared with a model employing no riometer data assimilation.|
|Rights:||©2016. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.|
|Description:||We acknowledge the efforts of Don Wallis who was principally responsible for the scientific operation of the CANOPUS riometer array and the NORSTAR team for providing the riometer data used in this study, which are available from ftp://aurora.phys.ucalgary.ca/data/riometer/. SGO riometer measurements are available from http://www.sgo.fi/Data/Riometer/rioData.php, and IRIS (Kilpisjärvi) riometer data are available from http://spears.lancs.ac.uk/data/request.html. NRCan riometer data are provided as a data set in the supporting information and are also available on request from Donald.Danskin@Canada.ca. We also acknowledge the U.S. National Geophysical Data Centre for providing GOES satellite data, available from http://satdat.ngdc.noaa.gov/sem/, and Kp geomagnetic and solar activity indices, available from ftp://ftp.ngdc.noaa.gov. Dst geomagnetic indices were provided by the World Data Centre for Geomagnetism, Kyoto (http://wdc.kugi.kyoto-u.ac.jp/dstdir/).|
|Appears in Collections:||Published Articles, Dept. of Engineering|
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