The core application of meteorological big data is forecasting.

The core application of meteorological big data is indeed forecasting. The specific analysis is as follows:

1. Accuracy of prediction: The prediction ability of meteorological big data is centered on its accuracy. Through the analysis of a large number of historical meteorological data, combined with modern numerical forecasting model, the meteorological department can predict the future weather trend more accurately. This accuracy not only helps to prepare for disaster prevention in advance, but also helps people to better plan their daily lives and travel.

2. Timeliness of forecast: With the development of big data technology, the timeliness of weather forecast has also been significantly improved. Now, the meteorological department can provide short-term, medium-term, long-term and even ultra-long-term weather forecasts to meet the needs of different users. The timeliness of this forecast has great application value in agriculture, transportation, energy and other fields.

3. The comprehensiveness of prediction: Meteorological big data can not only predict daily weather conditions, but also predict extreme weather events. For example, by analyzing a large number of meteorological data, the meteorological department can predict the occurrence probability and influence range of extreme weather such as hurricanes, rainstorms and floods, thus helping people to better cope with these disasters.

4. Sustainability of forecast: The application of meteorological big data is not one-off. It can continuously predict the future weather, and this prediction will become more accurate with the increase of data and the continuous update of the model. This persistence makes meteorological big data have high application value in long-term planning and decision-making.

Wide application of meteorological big data;

1. Agricultural field: In agricultural production, meteorological data is very important for making agricultural production plans and planting plans. By using meteorological data, farmers can better avoid environmental risks and improve agricultural production efficiency.

2. Traffic field: Meteorological data has important applications in road traffic and maritime traffic. For example, the meteorological department can provide information such as road humidity and road conditions to help drivers drive safely. In waterway transportation, the meteorological department can provide data such as waves and wind to help the crew make more accurate navigation decisions.

3. Energy field: Meteorological big data can help predict energy demand and supply. For example, in power system, forecasting power demand according to meteorological data can conduct power dispatching more effectively.

4. Public management: Meteorological big data is also widely used in public management. For example, in emergency management, the meteorological department can provide meteorological early warning to help the government better cope with disasters.

5. Scientific research and education: Meteorological big data also has important application value in scientific research and education. For example, researchers can use meteorological data to study climate change and ecological environment.