Excelsior Correspondent
NEW DELHI, Feb 6: Dr. Jitendra Singh, the Union Minister of State with Independent Charges for Science and Technology, Earth Sciences, the Prime Minister’s Office, the Department of Atomic Energy, the Department of Space, and Personnel, Public Grievances, and Pensions, announced today in the Rajya Sabha about the Union Cabinet’s endorsement of “Mission Mausam”.
In response to a query, the Minister elaborated that “Mission Mausam” is envisioned as a comprehensive and transformative initiative aimed at enhancing India’s capabilities in weather and climate research and services. It is set to better equip various stakeholders, including citizens and grassroots users, to confront extreme weather phenomena and the consequences of climate change. The primary goal of the Mission Mausam is to establish India as a “weather-ready and climate-smart” nation, with objectives such as (i) Strengthening observational capabilities (both in-situ & remote sensing), (ii) Enhancing understanding and application of Science, Innovation, Technology, and Data Science for societal welfare, (iii) Improving our Model/Data Assimilation/HPC for delivering accurate information to the Public and stakeholders (including Numerical+Artificial Intelligence and Machine Learning), (iv) Developing trained personnel in Earth System Science, (v) Forecast dissemination, and (vi) Fostering effective communication with society: Early Warning for ALL.
The initiative is being coordinated by the Ministry through its Research and Development institutions, which include the India Meteorological Department (IMD), the Indian Institute of Tropical Meteorology (IITM), and the National Centre for Medium Range Weather Forecasting (NCMRWF).
Dr. Jitendra Singh mentioned that the Mission Mausam aims to advance weather monitoring and forecasting capabilities throughout the nation and its neighboring areas.
It is anticipated that Mission Mausam will deliver precise forecasts across varying timelines, ranging from short-term weather predictions (hours to days) to medium-term forecasts (weeks) and extended (seasonal) predictions. This will be facilitated by deploying state-of-the-art observation systems, high-performance computing infrastructure, and sophisticated Earth system models. The incorporation of Artificial Intelligence (AI) and Machine Learning (ML) technologies will significantly refine prediction accuracy and enhance model resolution.
