تقرير
LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensembles
| العنوان: | LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensembles |
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| المؤلفون: | Guan, Haiwen, Arcomano, Troy, Chattopadhyay, Ashesh, Maulik, Romit |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science Physics (Other) |
| مصطلحات موضوعية: | Computer Science - Machine Learning, Physics - Atmospheric and Oceanic Physics, Physics - Computational Physics |
| الوصف: | We present LUCIE, a $1000$- member ensemble data-driven atmospheric emulator that remains stable during autoregressive inference for thousands of years without a drifting climatology. LUCIE has been trained on $9.5$ years of coarse-resolution ERA5 data with $4$ prognostic variables on a single A100 GPU for $2.4$ h. Owing to the cheap computational cost of inference, $1000$ model ensembles are executed for $5$ years to compute an uncertainty-quantified climatology for the prognostic variables that closely match the climatology obtained from ERA5. Unlike all the other state-of-the-art AI weather models, LUCIE is neither unstable nor does it produce hallucinations that result in unphysical drift of the emulated climate. Furthermore, LUCIE \textbf{does not impose} ``true" sea-surface temperature (SST) from a coupled numerical model to enforce the annual cycle in temperature. We demonstrate the long-term climatology obtained from LUCIE as well as subseasonal-to-seasonal scale prediction skills on the prognostic variables. We also demonstrate a $20$-year emulation with LUCIE here: https://drive.google.com/file/d/1mRmhx9RRGiF3uGo_mRQK8RpwQatrCiMn/view |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2405.16297 |
| رقم الأكسشن: | edsarx.2405.16297 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |