In this thesis, we use convolutional long short-term memory based neural network archi-
tectures to predict certain basic dynamics of weather variables. First, rainfall dynamics
are studied across direct and iterative ...
In this work, we use convolutional recurrent neural network-based architectures involving
ConvLSTM and ConvGRU for precipitation forecasting over the Indian region. We first
compare direct and iterative approach for ...
For any country, understanding and interpreting precipitation dynamics is of great importance. In India, rainfall patterns profoundly influence daily livelihoods and economic development. Thus, it is essential to get ...
Predicting the various oceanic parameters responsible for air-sea coupling is crucial to understanding how the climate and weather systems can affect the ecosphere. One of the most important among these oceanic parameters ...
Fire incidences have recently increased due to climate change and other human-induced factors. Due to incidents such as stubble burning in Punjab-Haryana, forest fires in various parts of India, like the north-east and ...