Auroral Precipitation Modeling Relevant to the Antarctic Upper Atmosphere

该奖项是为了进一步发展先进的极光粒子降水模型，其能量范围从几十电子伏到几百千电子伏，其中将包括明确的季节依赖性，从而可以分别预测南部和北方极地电离层的行为。该模型的参数化将通过函数拟合而不是通过少数几组具有实验数据的离散箱来实现。高能粒子的数量在不同的时间尺度上变化，比低能粒子的数量更深地渗透到地球的高层大气中，对大气化学的影响要深刻得多。通过分析美国航天局极地航天器UVI瞬时全球图像，将首次使用临近预报、基于Kp指数和太阳风/国际货币基金组织驱动的方法对降水模型进行定量比较。这项工作将使研究的多参数模型，结合太阳风数据和临近预报（或Kp，证明适当），以显着提高模型的准确性联合收割机。其他主要进展将包括提供详细的粒子谱而不仅仅是特征能量，并处理目前一代降水模型无法处理的高度扰动的地磁条件。目前正在对这一模式进行评估，以取代其旧的业务降水模式。这对地球空间科学界和监测空间气象的业务机构都很重要。本科生的参与扩大了该项目的教育组成部分。

This award is for further development of the advanced auroral particle precipitation model for the energy range from a few tens of electronvolts (eV) up to hundreds of kilioelectronvolts (keV) that will include explicit seasonal dependence permitting separate prediction of the behavior of the Southern and Northern polar ionospheres. The model's parameterization will be achieved through the functional fits rather than through a handful set of discrete bins with experimental data. The higher energy particle population, which varies on a different time scale than the lower energy particle population, penetrates deeper into the Earth's upper atmosphere, affecting atmospheric chemistry much more profoundly. For the first time the precipitation models will be quantitatively compared using the nowcast, Kp-index based, and solar wind/IMF-driven approaches through the analysis of the NASA'a Polar spacecraft UVI instantaneous global images. This work will enable investigations of the multi-parameter models that combine the solar wind data and nowcast (or Kp as proves appropriate) to improve significantly the model's accuracy. Other major advances will include providing detailed particle spectra instead of just characteristic energies, and to handle highly disturbed geomagnetic conditions that no current generation precipitation models can treat. The broader impacts of this modeling effort are achieved through the running the advanced precipitation models on the NOAA/NGDC Web site in real-time operation; this model is currently under evaluation to replace their old operational precipitation model. This is important for both the geospace scientific community and operational agencies monitoring space weather. Involvement of the undergraduate students extends the project's educational component.