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The India Meteorological Department (IMD) has made significant strides in improving the accuracy of weather forecasting, with a reported 40 to 50 percent increase in the precision of predictions for severe weather events over the past five years.

According to Union Minister of State for Science & Technology, Dr. Jitendra Singh, the advancements are a result of continuous upgrades to the IMD's weather monitoring systems. These improvements cover a wide range of weather phenomena, including heavy rainfall, fog, heatwaves, cold spells, and thunderstorms.

“Through enhanced meteorological observations, cutting-edge modeling tools, and the latest in data science, we have been able to improve the reliability of our weather forecasts,” Dr. Singh said in a written statement to the Rajya Sabha.

Leveraging AI, Machine Learning, and Remote Sensing

The IMD has incorporated state-of-the-art technologies to boost the accuracy of its predictions. Key tools now in use include sophisticated numerical weather prediction models with higher spatial and temporal resolution, as well as multi-model ensemble methods that combine forecasts from multiple sources. Additionally, the IMD has introduced artificial intelligence (AI), machine learning (ML), and data science methodologies to refine its forecasting capabilities.

These technological advancements are complemented by enhanced ground-based and upper-air observations, as well as a robust network of remote sensing tools that allow for real-time monitoring of weather conditions across the country.

The IMD has also improved its dissemination of early warnings, using tools such as the Common Alert Protocol (CAP), mobile applications, websites, and social media platforms to ensure timely communication with the public. These efforts are intended to help people better prepare for and respond to extreme weather events.