Project Abstract

Weather forecasting has always been a crucial aspect of human civilization, aiding in planning daily activities, agriculture, disaster management, and various industries. Over the years, different methods and models have been developed to predict weather patterns with increasing accuracy. This research abstract explores the various methods and applications of weather forecasting models. One of the most common methods used in weather forecasting is numerical weather prediction models. These models utilize mathematical equations to simulate the behavior of the atmosphere based on current weather conditions. By analyzing factors such as temperature, pressure, humidity, and wind patterns, numerical weather prediction models can forecast weather changes over a period of time. These models are constantly being improved with advancements in technology, leading to more accurate and reliable predictions. Another method widely used in weather forecasting is statistical forecasting. Statistical models analyze historical weather data to identify patterns and trends that can help predict future weather conditions. These models are particularly useful for short-term forecasts and are often used in conjunction with numerical weather prediction models to improve overall accuracy. Machine learning techniques have also been increasingly employed in weather forecasting. By training algorithms on vast amounts of weather data, machine learning models can identify complex relationships and patterns that may not be captured by traditional forecasting methods. These models can provide valuable insights into weather phenomena such as extreme events and climate change impacts. Furthermore, ensemble forecasting has gained popularity in recent years as a way to improve the reliability of weather predictions. Ensemble models run multiple simulations with slightly varied initial conditions to account for uncertainties in the atmosphere. By analyzing the range of outcomes from these simulations, forecasters can provide more probabilistic forecasts, giving users a better understanding of the potential risks associated with different weather scenarios. The applications of weather forecasting models are vast and diverse. From agricultural planning to aviation, energy management to disaster preparedness, weather forecasts play a critical role in decision-making processes across various sectors. By providing timely and accurate information, weather forecasting models help mitigate risks, optimize operations, and improve overall efficiency in numerous industries. In conclusion, the evolution of weather forecasting models has significantly enhanced our ability to predict and understand weather patterns. By combining different methods and techniques, forecasters can provide valuable insights into future weather conditions, enabling individuals and organizations to make informed decisions and adapt to changing environments.

Project Overview

Modern society’s ever-increasing demand for more accurate weather forecasts is evident to most people. The spectrum of needs for weather predictions ranges from the general publics desire to know if for instance, the weekend will permit an outing at the beach or an outdoor wedding reception. Such diverse industries as airlines and fruit growers depend heavily on accurate weather forecasts. In addition, in developed countries, the designs of buildings, smokestacks, and many industrial facilities rely heavily on a sound knowledge of the atmosphere.

Once an all-human endeavour based mainly upon changes in barometer pressure, current weather conditions and sky conditions, forecast models are now used to determine future conditions. Human input is still required to pick the best possible forecast model to base the forecast upon, which involves pattern recognition skills, knowledge of model performance and knowledge of model biases. The chaotic nature of the atmosphere, error involved in measuring the initial conditions, an incomplete understanding of atmospheric processes mean that forecast become less accurate as the difference in current time and the time for which the forecast is being made increases.

There are a variety of end users to weather forecasts. Weather warnings are important forecasts because they are used to protect life and property. Forecasts based on temperature and precipitation are important to agriculture, and therefore to commodity traders within stock markets. Temperature forecasts are also, used by utility companies to estimate demand over coming days. On an everyday basis people use weather forecasts to determine what to wear on a given day. Since in recent time especially in this part of the world, outdoor activities are severely curtailed by heavy rains, forecasts can be used to plan activities around these events, and to plan ahead and survive them.



Historical background
For millennia, people have tried to forecast the weather. In 650 BC, the Babylonians predicted the weather from cloud patterns as well as astrology. In about 340 BC, Aristotle described weather patterns in Meteorologica. Chinese weather prediction lore extends at least as far back as 300 BC.

Ancient weather forecasting methods usually relied on observed patterns of events, also termed pattern recognition. For example, it might be observed that if the subset was particularly red, the following day often brought fair weather. This experience accumulated over the generations to produce weather lore. However, not all of these predictions prove reliable, and many of them have since found not to stand up to rigorous statistical testing.

It was not until the invention of the electric telegraph in 1835 that the modern age of weather forecasting began. Before this time, it had not been possible to transport information about the current date of the weather any faster than a steam train. The telegraph allowed reports of weather condition from a wide area to be received almost instantaneously by the late 1840s. This allowed forecasts to be made knowing what the weather conditions were like further upwind. The two men most credited with the birth of forecasting as science were Francis Beaufort (remembered chiefly for the Beaufort Scale) and his protégé Robert FitzRoy (developer of the Fitzroy barometer). Both were influential men in British naval and governmental circles, and though ridiculed in the press at the time, their work gained scientific credence, was accepted by the Royal Navy, and formed the basis for all of today’s weather forecasting knowledge.

Great progress was made in the science of meteorology during the 20th century. The possibility of numerical weather prediction was proposed by the British mathematician Lewis Fry Richardson in 1922, though computers did not exist to complete the vast number of calculations required to produce a forecast before the event had occurred. The first successful numerical prediction was performed in 1950 by a team composed of the American meteorologists Jule Charney, Philip Thompson, Larry Gate, and Norwegian meteorologist Ragnar Fjortoft and applied mathematician John Von Neumann, using the ENIAC digital computer.







Aims and objectives
From current weather patterns a number of methods are used to determine the future state of atmosphere, a task generally called weather forecasting. The main aims and objectives of this research are as follows:



To provide an insight into what weather forecasting is all about,
To examine how models create forecasts,
To provide many methods used in modern weather prediction
To show different aspects of life where weather forecasts could be applied, and
To provide recommendations that would arouse the public’s interest in accurate weather forecasts.


Scope of study
This research is basically considering the various methods and applications of weather forecasting models with a review on how models create forecasts base on related literature.

1.4   Significance of the study

In view of the several severe adverse weather conditions experienced in recent times in the world over, and the numerous embarrassments experienced by the members of the public as a result of inaccurate prediction of future weather conditions, it is pertinent to take a look at the forecasting problems experienced by forecasters, which hinder accurate weather predictions.

Also, there is need to take a critical look at the different methods of weather forecasting and to provide relevant applications of these weather warnings.

Finally, the recommendations provided in their research will help encourage every direct user of weather predictions to adhere strictly to the warnings so as to avert certain mishaps or bitter experiences associated with adverse weather conditions.