论文标题
为太空天气驱动器的基准测试预测模型
Benchmarking Forecasting Models for Space Weather Drivers
论文作者
论文摘要
太空天气指数通常用于推动各种地理系统的运行预测，包括用于质量密度和卫星阻力的热层。这些驾驶员充当各种过程的代理，这些过程会导致地理空间系统中的能量流和沉积。中性质量密度的预测是对低地球轨道（LEO）物体的操作轨道预测和相撞避免的主要不确定性。对于强驱动的系统，太空气象驱动器预测的准确性对于操作至关重要。美国空军目前在运营环境中使用的高精度卫星阻力模型（HASDM）由四（4）个太阳能和两（2）个地磁代理驱动。太空环境技术（SET）由太空命令签约，以为驾驶员提供预测。这项工作对驾驶员预测模型的性能进行了全面评估。目的是为未来改进预测模型提供基准。使用跨越六（6）年的存档数据集和太阳周期24的15,000个预测，我们量化了模型性能的时间统计信息。
Space weather indices are commonly used to drive operational forecasts of various geospace systems, including the thermosphere for mass density and satellite drag. The drivers serve as proxies for various processes that cause energy flow and deposition in the geospace system. Forecasts of neutral mass density is a major uncertainty in operational orbit prediction and collision avoidance for objects in low earth orbit (LEO). For the strongly driven system, accuracy of space weather driver forecasts is crucial for operations. The High Accuracy Satellite Drag Model (HASDM) currently employed by the United States Air Force in an operational environment is driven by four (4) solar and two (2) geomagnetic proxies. Space Environment Technologies (SET) is contracted by the space command to provide forecasts for the drivers. This work performs a comprehensive assessment for the performance of the driver forecast models. The goal is to provide a benchmark for future improvements of the forecast models. Using an archived data set spanning six (6) years and 15,000 forecasts across solar cycle 24, we quantify the temporal statistics of the model performance.
