Conception of Indian Monsoon Prediction Methods
摘要
India is the largest economy of South Asia and a rising economy in the world. More than 20% of its bedrock is formed by the agriculture sector which is greatly impacted by the Indian monsoon. It plays a crucial role in the growth of several crops and water resources and decides many natural calamities like floods and droughts that can affect human beings severely. Therefore, the monsoon has been under research fraternity for centuries. With gradually rising temperatures and changing monsoon patterns, India is experiencing anomalies in precipitation occurrences. Intermittent intensified rain can cause engulfed floods, landslides, loss of farmer’s harvests, damaged roads and commuting problems that affect the common man every day. Similarly, many states faced water shortages leading to crop failure, starvation and spread of many diseases. Both excess and scarcity of rainfall can bring famine and result in a bad economy. All these consequences can be prevented if the onset of the monsoon can be estimated before its arrival. Therefore, this study is intended toward understanding the nature of monsoon and classification of methodologies implemented for its early prediction so far. Following an analysis of every model currently in use, it was discovered that deep learning models outperform all other models. However, as the monsoon is a complicated system of atmospheric and oceanic connection, it remains a matter of research to identify the points at which predictability weakens.