Forecast of Actionable Radiation Belt Scenarios

空间天气模型中的预报大多忽略了一切都是由太阳驱动的事实，这基本上是不可预测的。将观测到的太阳动力学传播到地球上是有问题的，这取决于我们无法约束其边界条件的模型。我们仅限于L1的数据，给出了一小时的提前期和神经网络类型的控制参数(例如Kp)预测，这些参数控制着我们最佳模型的物理特性。现在的预报更好：先进的数据同化技术与基于物理的模式在再现真实辐射带(RB)环境方面显示出极大的保真度。由于缺乏地球观测系统以外的高质量实时数据，这类现播的业务使用受到限制。法比斯项目则不同：它将其雄心限制在对卫星运营商有用的简单、可实现的预测目标上，同时避免了过去项目的陷阱。我们认为，虽然可能不可能准确预测空间天气事件的中断，但一旦事件开始，我们就有工具来预测后续行为，并在事件期间更新我们的预测。虽然我们可能不能在全球范围内详细预测随后的动态行为，但我们可以为卫星运营商提供几个关键事件特征的可行预测：a.最严重环境的时间b.最严重的通量达到c.事件结束的时间这些特征被ESWW16的航天器操作员代表认为最有用[http://www.stce.be/esww13/contributions/public/S5-O1/S5-O1-03-PitchfordDave/FORECASTINGTHEPERFECTSTORM.ppt].我们通过使用仅由简单、负担得起和可靠的地面实时输入驱动的基于物理的模型来克服数据同化Now cast的局限性，我们通过使用场景驱动的RB动力学预测方法来克服我们无法准确预测磁层驱动因素的问题，该方法从Now cast开始，并在事件期间通过实时模型输入的持续可用性不断改进。Workday项目设置完成

Forecast in Space Weather modeling mostly ignore the fact everything is driven by the sun, that is basically unpredictable. Propagating observed solar dynamics to Earth is questionable, it depends on models whose boundary conditions we are incapable of constraining. We are limited to data at L1, giving a one hour lead time and neural net type forecasts of controlling parameters ( e.g. Kp) that govern the physics of our best models. Nowcasts are better: advanced data assimilation techniques with physics based models show great fidelity in reproducing the real radiation belt (RB) environment. Operational use of such Nowcasts is limited by lack of high quality real-time data beyond GEOS. The FARBES project is different: it limits its ambition to simple, achievable prediction goals that are of utility to satellite operators, while avoiding the pitfalls of past projects. We hold that while it may be impossible to accurately predict the break of a space weather event, once an event has started we have the tools to predict subsequent behavior and to update our predictions during the event. While we may not be able to globally predict in detail the subsequent dynamic behavior, we can provide actionable forecasts for satellite operators on a few key event characteristics: a. Time to most severe environment b. Most severe Flux reached c. Time to the end of event These characteristics were deemed most useful by spacecraft operator representatives at ESWW16 [http://www.stce.be/ esww13/contributions/public/S5-O1/S5-O1-03-PitchfordDave/FORECASTINGTHEPERFECTSTORM.ppt]. We overcome the data assimilation nowcast limitations by using physics based models driven by simple, affordable and reliable ground-based real-time inputs only, we overcome our inability to accurately forecast magnetospheric drivers by using a scenario-driven forecast approach for RB dynamics starting with nowcast and is constantly refined during an event by the ongoing availability of real-time model inputs.Workday Project Setup Complete