Can signal-to-noise ratio indicate prediction skill? Based on skill assessment of 1-month lead prediction of monthly temperature anomaly over Japan
We present a skill assessment of 1-month lead deterministic predictions of monthly surface air temperature anomalies over most part of Japan based on a large-ensemble climate model, SINTEX-F. We found that September is the most predictable and the only month in which the prediction skill beats the p...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-09-01
|
| Series: | Frontiers in Climate |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fclim.2022.887782/full |