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Abstract

Over the last decade, an important development in the domain of climate forecasts, more specifically the prediction of weekly weather changes, has been performed with substantial accuracy. The phenomena is ascribed to more advanced strategies for accumulating and evaluating weather information, atmospheric conditions, the introduction of more potent NWP fashions, and large processing capacities. Long-term forecasting nevertheless faces difficulties due   to the   intricacy of weather structures in addition to complex records and over-fitting of current deep learning models