The Union Minister of Earth Sciences, Shri Kiren Rijiju, elucidated the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) within the domain of Earth Sciences. Highlighting the ongoing advancements, these technologies are dynamically shaping and redefining the landscape of weather, climate, and ocean forecasts across the diverse spectrum of institutes operating under the Ministry of Earth Sciences (MoES).
He emphasised the pivotal role played by AI and ML in reimagining the methodologies and precision levels involved in weather prediction, climate analysis, and oceanic forecasting. These technologies stand as the vanguard, offering innovative tools and methodologies that are actively modernising and enhancing the accuracy of predictive modelling and analytical techniques within MoES-supported institutions.
MoES has established a dedicated AI and ML virtual centre, a hub for developing, testing, and enhancing various techniques. This centre not only conducts workshops and conferences for capacity building but has also set up a specialised computing environment and virtual workspace on a Graphical processor-based server within the India Meteorological Department (IMD). This infrastructure serves as a training and deployment ground for AI models.
The outcomes of leveraging AI and ML in research and development within weather prediction are noteworthy:
- Enhanced precision in short-range precipitation forecasts spanning 1-day, 2-day, and 3-day lead times, effectively reducing bias.
- Creation of high-resolution (300m) urban gridded meteorological datasets for temperature and precipitation, empowering localised insights.
- Development of the time-varying Normalised Difference Urbanisation Index with a striking spatial resolution of 30 meters, encompassing data from 1992 to 2023.
- Establishment of very high-resolution precipitation datasets for meticulous verification purposes.
- An ongoing exploration of a Deep Learning approach for precipitation nowcasting, harnessing data from Doppler Weather Radars (DWRs).
MoES envisions a hybrid future where weather and climate forecasts will amalgamate AI/ML models with traditional numerical prediction models. This hybrid technology is poised to set new standards in forecast accuracy.
Encouragement for institutes under MoES to harness AI and ML in Earth Sciences remains consistent. In line with this, MoES remains committed to augmenting High-Performance Computing (HPC) infrastructure. The application of AI and ML-based data-driven modelling extends to generating species-specific Potential Fishing Sone (PFS) advisories, benefiting fishermen across coastal states.
The High-Performance Computing System (HPCS) under MoES aims to enhance weather and climate forecasting, providing services encompassing monsoon forecasts, ocean states, seismic activities, and Earth system phenomena.
With a focus on improving forecast accuracy, the HPCS utilises modern supercomputers and AI/ML algorithms to solve complex equations and models. Upgrading computational resources and models, increasing resolution, developing ensemble prediction models, and training skilled manpower are among the key initiatives.
ACROSS, which stands for Atmospheric, Climate Science and Services, comprises four key sub-schemes focusing on various aspects crucial to climate understanding and prediction.
MC4 aims to enhance databases and climate models to predict monsoonal changes better, improve climate modelling, study cloud dynamics, conduct ground-based measurements, and establish climate-related networks.
HPCS supports computational needs for climate modelling and data analysis. MM-II concentrates on enhancing weather and climate services by improving forecast systems and deploying Polarimetric Doppler Weather Radars (DWRs). The Atmospheric Observations Network focuses on upgrading forecast systems and boosting observational capabilities for studying atmospheric phenomena.
OpenGov Asia reported on the transformative potential of artificial intelligence (AI) in shaping India’s digital landscape, resonating with the groundbreaking advancements within Earth Sciences. Union Minister of State for Electronics and Information and Technology (MeitY), Rajeev Chandrasekhar, highlighted AI’s pivotal role in propelling growth across sectors like healthcare, agriculture, and governance, aligning with the significant strides made in weather, climate, and ocean forecasts powered by AI and ML.
