Bayesian Joint Probability Approach for Post‐Processing Monthly Precipitation Prediction in Northwest Iran
Abstract The probabilistic prediction of monthly precipitation events, specifically more‐than‐normal (MN), normal (N), and less‐than‐normal (LN) events, holds significant importance in the field of water resource management. In this paper, we employ the Bayesian Joint Probability (BJP) modeling appr...
| Published in: | Water Resources Research |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-08-01
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| Subjects: | |
| Online Access: | https://doi.org/10.1029/2023WR036846 |