Report
Dynamics of real-time forecasting failure and recovery due to data gaps
| العنوان: | Dynamics of real-time forecasting failure and recovery due to data gaps |
|---|---|
| المؤلفون: | Wu, Sicheng, Wang, Ruo-Qian |
| سنة النشر: | 2022 |
| المجموعة: | Nonlinear Sciences Physics (Other) |
| مصطلحات موضوعية: | Physics - Data Analysis, Statistics and Probability, Nonlinear Sciences - Chaotic Dynamics |
| الوصف: | Real-time forecasting is important to the society. It uses continuous data streams to update forecasts for sustained accuracy. But the data source is vulnerable to attacks or accidents and the dynamics of forecasting failure and recovery due to data gaps is poorly understood. As the first systematic study, a Lorenz model-based forecasting system was disrupted with data gaps of various lengths and timing. The restart time of data assimilation is found to be the most important factor. The forecasting accuracy is found not returning to the original even long after the data assimilation recovery. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2209.03413 |
| رقم الانضمام: | edsarx.2209.03413 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |