Seasonal Prediction of Atmospheric Rivers in the Western North Pacific Using a Seasonal Prediction Model
ABSTRACT Seasonal prediction of atmospheric rivers (ARs) in the western north Pacific (WNP) is examined using a seasonal prediction model with and without atmospheric initialisation. A 20‐year seasonal prediction was conducted to evaluate the model's prediction skill, particularly focusing over...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-05-01
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| Series: | Atmospheric Science Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/asl.1299 |
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| Summary: | ABSTRACT Seasonal prediction of atmospheric rivers (ARs) in the western north Pacific (WNP) is examined using a seasonal prediction model with and without atmospheric initialisation. A 20‐year seasonal prediction was conducted to evaluate the model's prediction skill, particularly focusing over the Japan area. The prediction skill of the present model indicated that the seasonal AR frequency is predictable with a lead time of up to 7–10 months, and the atmospheric initialisation further improved the skill. An additional investigation was conducted to identify the source of predictability for seasonal ARs. One significant source is the predictability of the Pacific‐Japan (PJ) pattern, which is influenced by the model's skill in predicting tropical sea surface temperature (SST) variability. The anticyclonic circulation southeast of Japan is well predicted when the tropical SST variability and PJ pattern are accurately predicted. Another source of predictability difference originated from the subsurface sea temperature (SBT) beneath the subtropical high in the North Pacific. When the SBT prediction is improved with atmospheric initialisation, it enhances the air‐sea interactions over the subtropical high in the WNP and southeast of Japan, leading to better predictability of seasonal ARs. |
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| ISSN: | 1530-261X |