The Department-related Parliamentary Standing Committee on Science & Technology, Environment, Forests and Climate Change considered the Demands for Grants (2020-21) of the Ministry of Earth Sciences in its meeting held on 17th February, 2020. During the meeting of the Committee held on 17th February 2020, the Secretary informed the Committee that the Ministry had proposed Rs.300 crore for Deep Ocean Mission proposed during the year 2020-21. However, no allocation had been made for the Mission during the year. The objective of the mission was underwater exploration and harnessing Ocean Resources. The Committee is in agreement with the Ministry that there is an urgent requirement to under take deep ocean research by India. As stated by the Secretary and acknowledged by the Committee, the monsoon is a critical factor for the livelihood and sustenance of crores of Indians, and it is determined not just by the land and atmospheric factors, but also the ocean. The Ministry has been trying to get funds allocated to the Mission for the past five years. Since the process for the initiation of the Mission has been set in motion after the in-principle approval by the Ministry of Finance, and the Ministry of Earth Sciences has already spent Rs.19 crore out of their own budget, the Committee is of the considered view that the Ministry should now be provided the requisite financial allocation for the Deep Ocean Mission during the current financial year and in future as well. The Committee was further informed that under the National Monsoon Mission program, advanced dynamical prediction systems have been developed for Seasonal prediction of Monsoon; Extended range prediction (for next 20 days) and Short & medium range (up to 10 days) weather prediction. In addition, a high resolution (12 km grid scale) state of the art Global Ensemble Prediction System (EPS) was commissioned on 01 June 2018, which is one of the best in the world. The Ensemble forecasts will enhance the weather information being provided by the current models by quantifying the uncertainties in the weather forecasts and generate probabilistic forecasts