Weather forecasting with data science approaches

Weather forecasting is a quite difficult task. The Wiki said, “ Weather forecasting is the application of science and technology to predict the conditions of the atmosphere for a given location and time. Weather forecasts are made by collecting quantitative data about the current state of the atmosphere at a given place and using meteorology to project how the atmosphere will change.”

So in general, weather forecasting is about the data about the atmosphere. Of course, I would not model the atmosphere condition, but I can use a lot of data about it for weather forecasting. In this article, I will try to predict the precipitation for the next 3 hours. I will try to solve this task in two ways — as a binary classification (1- precipitation, 0- no precipitation) and regression, where I will try to predict the amount of precipitation in mm.

So, what is precipitation? Let’s ask it in Wiki.” In meteorology, precipitation is any product of the condensation of atmospheric water vapor that falls under gravity. The main forms of precipitation include drizzle, rain, sleet, snow, graupel, and hail. Precipitation occurs when a portion of the atmosphere becomes saturated with water vapor so that the water condenses and “precipitates”. ” Let look at the schema, which shows the process of the water cycle and precipitation occurrence.

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