WEATHER FORECASTING: THE MODERN TOOL THAT CHANGED THE WORLD
The study of the discoveries, inventions, and technological advances has helped us to understand and predict the weather accurately. From simple observations made by early humans to early instruments such as thermometers and barometers to numerical prediction and satellite imaging, we’ll see how man has tried to harness weather.
In general, weather forecasts are made by collecting quantitative data about the present state of the atmosphere at a given place and using meteorology to project how the atmosphere will change. Which is all calculated by hand based mainly upon changes in air pressure, current climatic conditions, and sky condition or inclemency. But now the prognostication relies on computer-based models that take many atmospheric factors under consideration. Human input continues to be required to choose the simplest possible forecast model to base the forecast upon, which involves pattern recognition skills, teleconnections, knowledge of model performance, and knowledge of model biases. Also now with the assistance of AI weather predictions are more accurate than before.
Nearly In about 350 BCE, Aristotle has described the weather patterns in terms of Meteorological which implies studying the principle of meteorology and predicting the weather. Later, Theophrastus compiled a book on weather forecasting; called the Book of Signs where all the information gathered during his experiments associated with the weather was written. Also during the identical time Indian Astronomers develop their weather prediction methods consisting of inputs gathered from the behavior of patterns from stars and clouds which was more accurate than the other technology developed at that point. To calculate the sign of rain Indian Astronomers used lunar phases and forecast wind movements were taken into considerations.
Together with this the traditional forecasting methods also relied on observing patterns of events, which might even be termed pattern recognition. As an example, it would be observed that if the sunset was particularly red, the subsequent day often brought temperature. This experience was accumulated over the generations to provide weather lore. However, not all of those predictions prove reliable, and plenty of them have since been found to not arise to rigorous statistical testing.
It was a time of 1835 when the electrical telegraph was invented it led to the muse of recent age meteorology because before that the distant reports on weather prediction can cover a distance of a maximum of 160 km/day. But by the late 1840s, the telegraph allowed the reports of climate from a large area to be received almost instantaneously, allowing forecasts to be made of knowledge of climate further upwind predicting more accurate weather than before. The storm in 1859 that caused the loss of the charter inspired Fitzroy to develop fifteen land stations which started using telegraphic communication to transmit him the daily reports of weather at set times resulting in the primary gale warning service which was later used as a warning service for shipping.
In the late 20th century the advance in weather prediction takes place where the deep knowledge in atmospheric physics led to the muse of contemporary numerical weather prediction. This all happened in 1922 when an English scientist Lewis Fry Richardson published his book “Weather Prediction by Numerical Process”. during which he described how small terms within the prognostic fluid dynamics equations governing atmospheric flow may be neglected, and a finite differencing scheme in time and space may well be devised, allow numerical prediction solutions to be found.
The general idea of numerical weather prediction is to sample the state of the fluid at a given time and so use the equations of fluid dynamics and thermodynamics to estimate the state of the fluid at its slow within the future. Where the most inputs are obtained from different service stations based across the country, which may be a station along the surface or from automated weather stations at ground level over land and from weather buoys bewildered. Where the length of the time step is chosen within the model and is expounded to the space between the points on the computational grid, and is additionally chosen to take care of numerical stability. Time steps for global models are on the order of tens of minutes while time steps for regional models are between one and 4 minutes.
The latest research in predicting the weather using satellite imagery has shown immense benefit. With the assistance of it now we will access aviation problems like low clouds, monitoring thunderstorms, and tracking dust plumes. Where Multispectral composites combine satellite data collected at different wavelengths of the spectrum and present them as red-green-blue (RGB) images, which function enhanced representations of specific phenomena like low clouds and fog thus playing an enormous role in predicting the weather. In 2002, the ECU Organization for the Exploitation of Meteorological Satellites (EUMETSAT) led a shot to develop RGB products from the info collected by newly launched satellites. This produced a collection of best practices that included recipes for a collection of ordinary RGB products. Now with the assistance of this, the weather is predicted more accurately than the other technology developed before giving real-time data monitoring services. Also, the prediction of how dangerous a storm is often predicted in its initial phases which end up in evacuating people much before it hits.
The current development in AI weather prediction models shows great achievement as when it added with previous data and models a much more reliable and accurate information is obtained which can predict a storm, thunderstorm, rainfall, tsunamis and gives us the time to prepare for it. Also, nowadays every country has 4–5 metrological department across the country which keeps a close eye on wind speed and formation of clouds with the help of satellite imaginary technique and when this data is feed on to the machine it calculates all the prediction models with the help of which we can start preparing when it will be dangerous and how can we prepare for it. Thus the safety of all the people leaving across the coastal line or in a storm hit zone can be ensured.
