用深度光流替代传统追踪，高效生成全球高精度三维风场。
Distilling deep optical flow stereo methods to retrieve dense three-dimensional wind fields
- 用深度光流替代窗口匹配，提升立体测风效率与精度。
- 学生模型在水汽波段优于业务AMV，长波红外略降。
- 单卫星模型实现全盘覆盖，适合气象预报与数据同化。
静止大气运动矢量（AMVs）提供密集的水平风矢量（u, v）和高度，用于数据同化系统。传统AMVs通过窗口交叉相关追踪特征，并结合红外亮温与数值天气预报（NWP）背景状态估计高度，导致高度不准确、计算成本高且覆盖稀疏。GEO-GEO与GEO-LEO立体测风利用不同视角的视差几何解算高度，摆脱对NWP的依赖并提升精度，但计算负担重且覆盖有限。本文将立体匹配中的窗口追踪替换为深度光流，实现高效改进。通过自监督几何残差损失与有监督探空仪重建联合微调，平衡性能。为消除多卫星重叠需求，将立体教师模型蒸馏为单卫星学生模型。学生模型模拟教师的卡方检验与高度不确定性，用于质量控制。学生模型可生成全球全盘静止卫星图像的风场。验证对比了立体模型与学生模型在探空仪、业务AMV、ERA5再分析及EarthCARE云廓线上的表现。三重共检结果显示，立体风场在水汽波段（6.2、6.9和7.3 μm）优于业务AMV，长波红外（11.2 μm）性能下降。
原文摘要 · Abstract (English)
Geostationary atmospheric motion vectors (AMVs) provide the dense horizontal wind vectors (u,v) and heights ingested into data assimilation systems. Traditional AMVs track features using window-based cross-correlation and estimate heights via infrared brightness temperatures paired with numerical weather prediction (NWP) background states, creating a circular dependency that yields inaccurate heights, high computational cost, and sparse retrievals. Stereo winds from GEO-GEO and GEO-LEO geometrically resolve heights from parallax shifts across different poses, eliminating NWP dependence and improving accuracy, but they remain computationally heavy with limited coverage. In this work, we replace window-based tracking in stereo matching with deep optical flow for efficient, improved retrieval. Fine-tuning balances a self-supervised geometric residual loss with supervised radiosonde reconstruction. To eliminate multi-satellite overlap requirements, we distill the stereo teacher into a single-satellite student model. Chi-square and height uncertainties from the teacher are emulated by the student for quality assurance. The student generates winds across full-disk GEO imagery globally. Validation compares stereo and student models against radiosondes, operational AMVs, ERA5 reanalysis, and EarthCARE cloud profiles. Results through triple collocation show that stereo winds improve performance beyond operational AMVs for water vapor bands (6.2, 6.9, and 7.3 {\mu}m), wit degradation in the long-wave infrared (11.2 {\mu}m) band.
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