Owens M J, Riley P, Horbury T S
1Space and Atmospheric Electricity Group, Department of Meteorology, University of Reading, Earley Gate, PO Box 243, Reading, RG6 6BB UK.
2Predictive Science Inc., 9990 Mesa Rim Rd, Suite 170, San Diego, CA 92121 USA.
Sol Phys. 2017;292(5):69. doi: 10.1007/s11207-017-1090-7. Epub 2017 Apr 19.
Effective space-weather prediction and mitigation requires accurate forecasting of near-Earth solar-wind conditions. Numerical magnetohydrodynamic models of the solar wind, driven by remote solar observations, are gaining skill at forecasting the large-scale solar-wind features that give rise to near-Earth variations over days and weeks. There remains a need for accurate short-term (hours to days) solar-wind forecasts, however. In this study we investigate the analogue ensemble (AnEn), or "similar day", approach that was developed for atmospheric weather forecasting. The central premise of the AnEn is that past variations that are analogous or similar to current conditions can be used to provide a good estimate of future variations. By considering an ensemble of past analogues, the AnEn forecast is inherently probabilistic and provides a measure of the forecast uncertainty. We show that forecasts of solar-wind speed can be improved by considering both speed and density when determining past analogues, whereas forecasts of the out-of-ecliptic magnetic field [ ] are improved by also considering the in-ecliptic magnetic-field components. In general, the best forecasts are found by considering only the previous 6 - 12 hours of observations. Using these parameters, the AnEn provides a valuable probabilistic forecast for solar-wind speed, density, and in-ecliptic magnetic field over lead times from a few hours to around four days. For , which is central to space-weather disturbance, the AnEn only provides a valuable forecast out to around six to seven hours. As the inherent predictability of this parameter is low, this is still likely a marked improvement over other forecast methods. We also investigate the use of the AnEn in forecasting geomagnetic indices Dst and Kp. The AnEn provides a valuable probabilistic forecast of both indices out to around four days. We outline a number of future improvements to AnEn forecasts of near-Earth solar-wind and geomagnetic conditions.
有效的空间天气预测和缓解需要对近地太阳风状况进行准确预报。由远程太阳观测驱动的太阳风数值磁流体动力学模型，在预测导致近地几天和几周内变化的大规模太阳风特征方面的技能正在提高。然而，仍然需要准确的短期（数小时至数天）太阳风预报。在本研究中，我们研究了为大气天气预报开发的相似系综（AnEn）或“相似日”方法。AnEn的核心前提是，与当前状况相似或类似的过去变化可用于对未来变化提供良好估计。通过考虑过去相似情况的集合，AnEn预报本质上是概率性的，并提供了预报不确定性的一种度量。我们表明，在确定过去的相似情况时同时考虑速度和密度，可以改善太阳风速的预报，而通过同时考虑黄道内磁场分量，黄道外磁场[ ]的预报也会得到改善。一般来说，仅考虑前6 - 12小时的观测可得到最佳预报。使用这些参数，AnEn可为数小时至约四天的提前期内的太阳风速、密度和黄道内磁场提供有价值的概率预报。对于对空间天气扰动至关重要的[ ]，AnEn仅能提供约六至七小时的有价值预报。由于该参数的固有可预测性较低，这仍可能比其他预报方法有显著改进。我们还研究了AnEn在预报地磁指数Dst和Kp方面的应用。AnEn可为这两个指数提供约四天的有价值概率预报。我们概述了对近地太阳风和地磁状况的AnEn预报未来的一些改进。
