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In this article, we explored the performance of several fusion strategies for bias correction of precipitation on U‐Net‐based‐models and proposed a simple but efficient hybrid fusion strategy. The geopotential, vertical velocity, specific humidity and 3‐h cumulative precipitation from Yin‐He global spectral model (YHGSM) re‐forecast products are used as multiple correction factors, and the 3‐h cumulative...
In this paper, a data‐driven bias correction approach based on deep learning is proposed, which is appropriate for the Yin–He global spectral model (YHGSM) re‐forecasting. The proposed architecture involves four U‐Net‐based networks estimating the proper bias correction models for YHGSM re‐forecasting that consider as correction factors the geopotential, specific humidity, and vertical velocity on...
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