长期台风路径预测：一种无需再分析数据的物理条件约束方法
Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data
- SI Analytics
- The University of Manchester（曼彻斯特大学）
- Gwangju Institute of Science and Technology（光州科学技术院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对传统物理模型计算量大、现有数据驱动方法依赖非实时再分析数据难以满足72小时以上台风路径预测需求的问题，提出利用实时UM数据的物理条件约束方法，性能优于现有最优方法，并发布配套PHYSICS TRACK数据集。
AI中文摘要：
面对日益加剧的气候变化，台风强度及其造成的破坏已大幅上升。准确的路径预测对于有效控灾至关重要。传统的基于物理的模型虽然全面，但计算量大，且严重依赖预报员的专业知识。当前的数据驱动方法通常依赖再分析数据，这类数据被认为最接近天气状况的真实表征。然而，再分析数据并非实时生成，需要时间进行调整，因为预测模型需用观测数据校准。诸如ERA5这类再分析数据在具有挑战性的现实场景中存在不足。最优的防灾准备需要至少提前72小时的预测，这超出了标准物理模型的能力范围。针对这些限制，我们提出了一种利用实时Unified Model（UM，统一模型）数据的方法，规避了再分析数据的局限性。我们的模型以6小时为间隔提供最长提前72小时的预测，性能优于当前最优的数据驱动方法和数值天气预报模型。为助力减轻台风造成的灾害，我们发布了预处理后的PHYSICS TRACK数据集，其中包含ERA5再分析数据、台风最佳路径数据和UM预报数据。
英文摘要：
In the face of escalating climate changes, typhoon intensities and their ensuing damage have surged. Accurate trajectory prediction is crucial for effective damage control. Traditional physics-based models, while comprehensive, are computationally intensive and rely heavily on the expertise of forecasters. Contemporary data-driven methods often rely on reanalysis data, which can be considered to be the closest to the true representation of weather conditions. However, reanalysis data is not produced in real-time and requires time for adjustment because prediction models are calibrated with observational data. This reanalysis data, such as ERA5, falls short in challenging real-world situations. Optimal preparedness necessitates predictions at least 72 hours in advance, beyond the capabilities of standard physics models. In response to these constraints, we present an approach that harnesses real-time Unified Model (UM) data, sidestepping the limitations of reanalysis data. Our model provides predictions at 6-hour intervals for up to 72 hours in advance and outperforms both state-of-the-art data-driven methods and numerical weather prediction models. In line with our efforts to mitigate adversities inflicted by \rthree{typhoons}, we release our preprocessed \textit{PHYSICS TRACK} dataset, which includes ERA5 reanalysis data, typhoon best-track, and UM forecast data.
