Nowadays we pick up our mobile every morning and check today it will rain or not. And we sometimes find notifications that we should carry an umbrella today. Do you know how our mobile gives meteorological warnings for rain? And how our mobile suggests carrying an umbrella before going outside the house? It is nothing but mathematics that predicts the weather. Maths is so important in our life that we use it from the moment we get up from bed until we go back to bed. As we discover more and more about nature we find maths as a universal language because nature can be described mathematically. There is a very essential role of math in weather forecasting because of the fundamentals of mathematics used in forecasting the weather. Weather prediction uses mathematical models of oceans and the atmosphere to predict the weather based on the current weather conditions of a specific place and time.

Predicting the weather for tomorrow or the next 10 days is not an easy task. It is a combined effort of scientists, mathematicians, meteorologists, etc who are researching worldwide to predict the weather conditions of a place using foolproof ways or models. Though in recent years, weather forecasting has become more accurate, thanks to supercomputers, data scientists, and machine learning algorithms. They have made the job a lot quicker and more accurate. In this article, we will discuss the role of mathematics in accurately forecasting the weather.

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Weather Forecasting

Since ancient times, human beings have tried to predict weather conditions locally. But the 19th century has seen a deviation from informal weather prediction to formal and accurate weather prediction. Thanks to technological advancements. Supercomputers have the capability of quickly learning and thus getting attention in the weather forecasting arena. Supercomputers can process approximately 2.8 quadrillion mathematical calculations every second, and can predict weather in the near future. Let us go on to discuss step by step guides on how the weather forecasting model works.

Data collection

This is one of the most crucial parts of weather prediction. With help of modern communication systems, innovative devices, compressed monitoring networks, and highly-trained observers, data collection has become more detailed and accurate. Billions of earthly weather information like temperature, air pressure, humidity, wind speed, water levels, and many more are collected every day and brought together by supercomputers which are divided into the following two parts.

• Surface weather observations – these are important data that are manually by the retained observers. These data are used to issue meteorological warnings and for climatological purposes to predict weather conditions.

• Upper-air weather observations – Radiosondes generally obtain this data on aircraft, satellites, weather balloons, and radar. They collect data like humidity, wind, and temperature.

Data Analysis

In this process, collected data is processed. Data analysts or scientists use exploratory data analysis to find some correlation between collected data and weather conditions. They use some technology like Python for data analysis. These observations are then plugged into a series of mathematical algorithms that predict the weather. Mathematics concepts like linear regression are very useful for data analysis.

Linear Regression

The slope-intercept form of the equation of a line is Y = MX + C. Here X is the independent variable and Y is the dependent variable whose value depends on the value of X. M is the slope and C is the intercept on the Y axis.

Independent Variables like temperature, humidity, etc can be represented using this linear equation. Using a test data set we can generate a linear regression and validate it with another data set. Using this linear regression we can forecast the rain.

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Maths Concepts

Statistics: Data scientists use modelling and forecasting particularly in the progression of meteorological parameters as a function of time series. For example estimation of temperature trends for past and present. Compared to forecasting and prediction can be seen. Concepts of statistics are used in the prediction and forecasting of rain in a particular area using meteorological parameters like wind, temperature, humidity, precipitation, etc.

Probability: Our phone notifies us that there is a 50% chance of rain this means the likelihood of rain is 50 %. The probability forecast includes the numerical uncertainty of the event.

This kind of near-future weather prediction is known as numerical weather prediction. Thanks to the technological advancement to precisely predict the weather. Hope this article answers how our mobile suggests carrying an umbrella before going outside the home as well as how essential mathematics is for weather forecasting.