الملخص
The subseasonal-to-seasonal (S2S) timescale, roughly from two weeks to two months ahead, is a critical forecast window for sectors such as agriculture, energy, and water management. Yet, it is widely known as the `predictability desert'. Recent AI weather models excel up to two weeks ahead but deteriorate beyond, largely because they are trained to predict fine-scale details that are neither predictable nor essential at S2S timescales. We argue that a more physically grounded objective is to forecast only the slowly varying components that remain predictable. Computer vision reached the same conclusion with the Joint-Embedding Predictive Architecture (JEPA), which predicts in latent space, discarding unpredictable details. In this work, we introduce S2S-JEPA, which brings the JEPA paradigm to S2S forecasting. It is tailored to this task through design elements from state-of-the-art AI weather models. S2S-JEPA achieves comparable skill to the gold-standard ECMWF physics-based ensemble and surpasses it on multiple metrics at weeks 5 to 6.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Dong, C., & Mengaldo, G. (2026). S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales. https://omanscience.com/ar/articles/s2s-jepa-predicting-the-predictable-at-subseasonal-to-seasonal-timescales
MLA 9
Dong, Chenyu, and Gianmarco Mengaldo. "S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales." https://omanscience.com/ar/articles/s2s-jepa-predicting-the-predictable-at-subseasonal-to-seasonal-timescales.
شيكاغو (المؤلف–التاريخ)
Dong, Chenyu, and Gianmarco Mengaldo. 2026. "S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales." https://omanscience.com/ar/articles/s2s-jepa-predicting-the-predictable-at-subseasonal-to-seasonal-timescales.
هارفارد
Dong, C. and Mengaldo, G. (2026) 'S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales', Available at: https://omanscience.com/ar/articles/s2s-jepa-predicting-the-predictable-at-subseasonal-to-seasonal-timescales.
فانكوفر
Dong C, Mengaldo G. S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales. https://omanscience.com/ar/articles/s2s-jepa-predicting-the-predictable-at-subseasonal-to-seasonal-timescales
IEEE
C. Dong, and G. Mengaldo, "S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales," https://omanscience.com/ar/articles/s2s-jepa-predicting-the-predictable-at-subseasonal-to-seasonal-timescales.