How does the weather forecast predict rain and snow? What's the difference between them?

Weather forecast is based on meteorological observation data, using the principles and methods of meteorology, dynamics and statistics to make a qualitative or quantitative forecast of the weather conditions in a certain area or a certain place in the future. Accurate weather forecast has always been an important goal of atmospheric science research. Weather forecast is based on meteorological observation data, using the principles and methods of meteorology, dynamics and statistics to make a qualitative or quantitative forecast of the weather conditions in a certain area or a certain place in the future. Accurate weather forecast has always been an important goal of atmospheric science research. Knowing the weather from clouds → inferring the weather from objects → single station forecast → weather map forecast → application of meteorological satellites and weather radar → computer forecast. With the continuous progress of science and technology, weather forecasting has developed rapidly.

According to the prediction time limit, it can be roughly divided into: imminent earthquake prediction (1 ~ 2 hours), extremely short-term prediction (2 ~ 12 hours), short-term prediction (12 ~ 48 hours), medium-term prediction (3 ~ 10 days) and long-term prediction (.

Weather forecast method (or weather map method): a method of making weather forecast with weather map, satellite cloud map and radar map as the main tools. Analyze and study the changing law of weather with the principle of meteorology. This method is mainly used for short-term forecasting.

Numerical forecast method (also known as dynamic forecast method): a method of weather forecast by solving the dynamic equation describing atmospheric motion with a large-scale fast computer. This method can be used for both short-term and medium-and long-term forecasting. In recent years, it has also been used for climate prediction.

Statistical forecasting method: based on a large number of long-term meteorological observation data, according to the principle of probability statistics, find out the statistical law of weather change, establish the statistical model of weather change, and make the weather forecast method. This method is mainly used for medium and long-term forecasting and meteorological element forecasting. Why is the weather forecast inaccurate? As a science, weather forecast is still young, and its accuracy depends on the density of observation data. However, there are only 100 sounding stations in China, which is equivalent to only one sounding station every 200 kilometers. The observatory is like a dot in the net. The larger the network, the fewer the points, the greater the gap between points, and the higher the probability of missed detection and false detection. China has a vast territory and limited funds for meteorological observation, so it is inevitable that there will be false positives and false negatives. Modern weather forecast has five components: the most traditional data collected by professionals, amateurs, automatic weather stations or buoys on the ground or at sea are data such as air pressure, temperature, wind speed, wind direction and humidity. The World Meteorological Organization coordinates the timing of these data collections and sets standards. These measurements are made every hour (METAR) or every six hours (SYNOP). Using weather balloons, meteorologists can also collect the temperature, humidity and wind force values in the sky. Weather balloons can rise all the way to the tropopause. Data from meteorological satellites are becoming more and more important. Meteorological satellites can collect data from all over the world. Their visible photos can help meteorologists study the development of clouds. Their infrared data can be used to collect the temperature of the ground and cloud top. By monitoring the development of clouds, we can collect the wind speed and direction at the edge of clouds. However, because the accuracy and resolution of meteorological satellites are not good enough, ground data is still very important. Weather radar can provide information about precipitation area and intensity. Doppler radar can also measure wind speed and direction. Data Assimilation In the process of data assimilation, the collected data are combined with the numerical model used for forecasting to produce meteorological analysis. The result is the best estimate of the current atmospheric state, which is a three-dimensional representation of temperature, humidity, air pressure, wind speed and direction. Data weather forecast Digital weather forecast uses computers to simulate the atmosphere. Based on the results of data assimilation, it calculates the changes of the atmosphere with time according to the results of physics and fluid mechanics. Because the equations of fluid mechanics are very complicated, digital weather forecast can only be carried out by supercomputers. The output calculated by this model is the basis of weather forecast. In the past, meteorologists had to do their own processing work, but today's weather forecast over 24 hours mainly uses a variety of different models to synthesize the results. Meteorologists must also analyze the predicted model data so that end users can understand it. In addition, the resolution of weather forecast models is generally not particularly high. Local meteorologists must also consider the influence of the region through local experience to make the local weather forecast more accurate. However, with the continuous refinement of the weather forecast model, this workload is getting smaller and smaller. In the whole process, the presentation of weather forecast is the most important for the end users. Only by knowing what information the end user needs and how to convey it to the end user easily can this task be completed.