A New Statistical Model of Convection Based on Referencing SuperDARN Velocity Data to Auroral Arc Boundaries Determined from Polar UVI Observations
J. Michael RUOHONIEMI.
The Johns Hopkins University/Applied Physics Laboratory, USA.
Statistical models of convection continue to find important research applications. In the 1990s several new models were derived using quite different data sets and analysis techniques. These largely agreed on essential aspects of the IMF dependence of the global convection pattern. The development of SuperDARN has provided us with the opportunity of testing the predictions of these models for quasistatic conditions against observations. We have found a significant discrepancy, namely, the inability of the newer models to reproduce the sharp structures and boundaries of the convection pattern. It is probable that the variability of the pattern even under stable IMF conditions causes the smaller-scale structure to smear out in the course of averaging. We have begun the derivation of a new statistical convection model based on the large set of velocity data collected with the SuperDARN radars. We are exploring the value of scaling the velocity data using the location of auroral arc boundaries as determined by Polar UVI observations. In this talk we present examples of the new statistical patterns and discuss the improvement in resolution of structure that results from properly locating the velocity data within the auroral geometry.
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