India’s weather scientists are stepping into the future by harnessing the power of artificial intelligence (AI) and machine learning (ML) to revolutionize weather forecasts, according to Mrutyunjay Mohapatra, Director General of the India Meteorological Department (IMD). In a recent conversation with PTI editors, Mohapatra explained that AI and ML will complement the current numerical weather forecasting models and significantly enhance forecasting techniques in the coming years.
The IMD has been striving to improve its observational systems to provide mesoscale weather forecasts for smaller areas, such as panchayats covering around 10 square kilometers. To support these efforts, the IMD has deployed a network of 39 doppler weather radars that cover 85% of the country’s landmass. These radars enable hourly forecasts for prominent cities, ensuring more accurate and localized predictions.
Mohapatra emphasized that AI will play a crucial role in analyzing the IMD’s extensive digitized weather records dating back to 1901. By harnessing AI, scientists can sift through this vast amount of historical data to generate valuable insights about weather patterns. Unlike traditional physics-based models, AI models in weather forecasting focus on data science and utilize past data to make better forecasts.
To exploit the full potential of AI, expert groups have been formed by the Ministry of Earth Sciences and the IMD. Mohapatra emphasized that both AI and numerical forecasting models will work hand in hand and complement each other. He further explained that the goal is to provide hyper-localized forecasts, tailoring weather information to the specific needs of sectors like agriculture, health, urban planning, hydrology, and environment at the panchayat or village level.
Incorporating AI and ML into weather forecasting allows for more data-driven decision-making in an era of information abundance. Mohapatra stated that by leveraging past data, AI and ML can extract valuable insights and improve forecasting accuracy. This approach ensures that forecasting accuracy is not solely reliant on traditional physics-based models.
Moreover, climate change has resulted in the emergence of mesoscale phenomena like convective clouds. These small-scale weather patterns have a significant impact on local communities. To address this challenge, the IMD strategically deployed Doppler weather radars covering 85% of the country. With a high resolution of 350 meters per pixel, these advanced radars enable the detection and simulation of convective clouds, improving forecasting accuracy for extreme events like heavy rainfall and cyclones.
With the integration of AI and ML, the future of weather forecasting in India looks promising. These advanced technologies will enhance the accuracy, localization, and sector-specific tailoring of forecasts, ensuring that India stays well-prepared for any weather-related challenges.
FAQs
1. How does artificial intelligence enhance weather forecasting?
Artificial intelligence utilizes past data to generate knowledge that can be used to make better forecasts. It focuses on data science modeling rather than the physics of weather phenomena, allowing for more accurate predictions.
2. How can AI complement numerical forecasting models?
AI and numerical forecasting models work together to improve forecast accuracy. AI analyzes past data and provides valuable insights, while numerical models incorporate physics-based models to predict weather conditions.
3. What is the significance of hyper-localized forecasts?
Hyper-localized forecasts provide predictions at a more localized level, such as panchayats or villages. This tailors weather information to specific sectors like agriculture, health, urban planning, hydrology, and environment, enabling better decision-making and preparedness.
4. How do Doppler weather radars improve forecasting accuracy?
Doppler weather radars can detect and simulate convective clouds with a high resolution, significantly enhancing forecast accuracy for extreme events like heavy rainfall and cyclones. By strategically deploying these radars, the IMD can cover a large portion of the country and provide more precise predictions.
Sources:
– India Meteorological Department (IMD): https://imd.indianmeteorology.org/
India’s weather forecasting industry is set to experience a significant transformation with the integration of artificial intelligence (AI) and machine learning (ML) technologies. Mrutyunjay Mohapatra, Director General of the India Meteorological Department (IMD), has stated that AI and ML will complement existing numerical weather forecasting models and greatly enhance forecast accuracy in the coming years.
The IMD has been actively working to improve its observational systems to provide mesoscale weather forecasts for smaller areas, such as panchayats covering around 10 square kilometers. To support this effort, the IMD has deployed a network of 39 doppler weather radars that cover 85% of the country’s landmass. These radars enable hourly forecasts for prominent cities, ensuring more precise and localized predictions.
AI will play a crucial role in analyzing the IMD’s extensive digitized weather records that date back to 1901. By leveraging AI, scientists can uncover valuable insights from this vast amount of historical data, enabling a better understanding of weather patterns. Unlike traditional physics-based models, AI models in weather forecasting focus on data science and utilize past data to improve forecast accuracy.
To fully exploit the potential of AI in weather forecasting, expert groups have been formed by the Ministry of Earth Sciences and the IMD. The goal is to achieve hyper-localized forecasts tailored to the specific needs of sectors like agriculture, health, urban planning, hydrology, and environment at the panchayat or village level. By incorporating AI and ML technologies, decision-makers can make more data-driven decisions in an era of abundant information.
The integration of AI and ML into weather forecasting addresses the challenge posed by climate change and the emergence of mesoscale phenomena like convective clouds. These small-scale weather patterns have a significant impact on local communities. The strategic deployment of Doppler weather radars by the IMD, which provide a high resolution of 350 meters per pixel, allows for the detection and simulation of convective clouds, improving forecast accuracy for extreme events such as heavy rainfall and cyclones.
With the integration of AI and ML, the future of weather forecasting in India looks promising. These advanced technologies will enhance the accuracy, localization, and sector-specific tailoring of forecasts, ensuring that India remains well-prepared for any weather-related challenges.
FAQs:
1. How does artificial intelligence enhance weather forecasting?
Artificial intelligence utilizes past data to generate knowledge that can be used to make better forecasts. It focuses on data science modeling rather than the physics of weather phenomena, allowing for more accurate predictions.
2. How can AI complement numerical forecasting models?
AI and numerical forecasting models work together to improve forecast accuracy. AI analyzes past data and provides valuable insights, while numerical models incorporate physics-based models to predict weather conditions.
3. What is the significance of hyper-localized forecasts?
Hyper-localized forecasts provide predictions at a more localized level, such as panchayats or villages. This tailors weather information to specific sectors like agriculture, health, urban planning, hydrology, and environment, enabling better decision-making and preparedness.
4. How do Doppler weather radars improve forecasting accuracy?
Doppler weather radars can detect and simulate convective clouds with a high resolution, significantly enhancing forecast accuracy for extreme events like heavy rainfall and cyclones. By strategically deploying these radars, the IMD can cover a large portion of the country and provide more precise predictions.
Sources:
– India Meteorological Department (IMD): imd.indianmeteorology.org
The source of the article is from the blog queerfeed.com.br