In this study, a multiscale long short-term memory model with attention mechanism (MLSTM-
AM) is proposed to improve the accuracy of monthly precipitation forecasting. In the MLSTM …

Rainfall variability associated with the South Asian Summer Monsoon has increased in
recent decades, particularly at the northwestern monsoon margins over Pakistan, leading to …

Climate indices characterize climate systems and may identify important indicators for long-
term precipitation, which are driven by climate interactions in atmosphere-ocean circulation …

Drought is defined as a prolonged regional precipitation deficiency. Significant drought
conditions often occur during spring in South Korea since abundant water resources are …

Drought prediction is crucial for early risk assessment, preventing negative impacts and the
timely implementation of mitigation measures for sustainable water management. This study …

In this study, a multilevel temporal convolutional network (MTCN) model is proposed for 1-
month-ahead forecasting of precipitation. In the MTCN model, à trous wavelet transform …

To address the challenge of limited training samples, this study employs the model-agnostic
meta-learning (MAML) algorithm along with domain-knowledge-based data augmentation to …

Uncertainty in weather conditions for the forthcoming growing season influences farmers'
decisions, based on their experience of the past climate, regarding the reduction of …

In recent years, the damages resulting from abnormal hydrometeorological climate have
substantially increased over the world due to the climate variability and change. Especially …

In this study, long-term precipitation forecasting models capable of reflecting constantly
changing climate characteristics and providing forecasts for up to 12 months in advance …