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New deep learning model Dense-Cast forecasts precipitation with high accuracy

Researchers have developed Dense-Cast, a new lightweight deep learning model designed for short-term precipitation nowcasting. The model integrates DenseNet architecture, residual connections, and transformer encoders to effectively predict precipitation with fewer parameters. Tested in the monsoon-prone North-Eastern region of India, Dense-Cast uses historical precipitation data to forecast the next two half-hours. It achieved a best MAE of 0.235 mm, RMSE of 0.735 mm, and KGE score of 0.816. AI

IMPACT This model could improve disaster management and preparedness through more accurate short-term precipitation forecasting.

RANK_REASON Publication of a research paper detailing a new deep learning model. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

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New deep learning model Dense-Cast forecasts precipitation with high accuracy

COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Gourav Jyoti Kalita, Hidam Kumarjit Singh ·

    Dense-Cast: A lightweight ensemble of deep learning architectures for precipitation nowcasting

    arXiv:2608.06082v1 Announce Type: new Abstract: Proper short-term forecasting of precipitation is crucial in disaster management and preparedness. Nonetheless, the variability and nonlinearity of precipitation make short-term forecasting challenging for meteorologists. Moreover, …