News Excerpt:

The Ministry of Agriculture & Farmers Welfare have initiated the weather information network and data system (WINDS) to generate long-term, hyperlocal weather data.

Weather forecasting in India:

• In India, the Indian Meteorology Department (IMD) is the principal government agency in all matters relating to meteorology. 
• It specializes in the incredibly complex science of predicting weather patterns by observing, modeling and interpreting a multitude of variables.
• Currently, IMD operates around 800 automatic weather stations (AWS), 1,500 automatic rain gauges (ARG) and 37 Doppler weather radars (DWR). 
• This is against the total requirements of more than 3,00,000 ground stations (AWS/ARG) and around 70 DWRs. 
• In tropical countries like India, weather variability is inherently higher.
• Accurately predicting rain, cyclones, heatwaves and drought are critical to inform decision-making on disaster management.

About the WINDS system:

• The system will promote the data for wider agriculture and other sectors applications.
• It will help create a national-level database and assist in establishing the protocols required to access the country-wide data by the various public and private concerns.
• Under this programme, more than 200,000 ground stations (AWS and ARG) will be installed, which can help enhance weather data utilisation and thus improve weather predictions and decision-making.

Future prospects regarding weather forecasting systems in India:

• Through Make in India initiatives, many Indian companies have started manufacturing low-cost and highly reliable sensor-based air quality monitoring systems. 
  • These are also easy to install and have low maintenance costs. 
• The IITs are helping as well, as they have started centres of excellence in this domain with a mission to establish a nationwide network of affordable air quality sensors. 
• An integrated AI/ML-based model with data from the new air quality and weather sensors will be a major step forward in accurately predicting fog.
  • It will help in timely decision-making around transportation and the health-related impacts of air pollution.