Weather forecasting

Weather Forecasting: A Journey Through Time

Imagine trying to predict the weather without any modern technology or tools—how would you do it?

Ancient civilizations relied on observing patterns in nature, such as animal behavior and cloud formations. The Babylonians, Aristotle, and others contributed significantly to early methods of predicting weather, but formalized forecasting didn’t begin until the 19th century.

From Telegraphs to Modern Models

The invention of the electric telegraph in 1835 revolutionized communication. By the late 1840s, telegraph reports allowed for almost instantaneously received weather conditions from a wide area, enabling forecasts to be made based on upwind knowledge.

Francis Beaufort and Robert FitzRoy further developed forecasting as a science. Beaufort created the Wind Force Scale and Weather Notation coding, while FitzRoy led the collection of weather data at sea and developed charts for predicting storms. His efforts culminated in the first gale warning service established in 1861.

Advancements in Technology

The 20th century saw significant advancements with atmospheric physics leading to modern numerical weather prediction. Lewis Fry Richardson published ‘Weather Prediction By Numerical Process’ in 1922, laying the groundwork for computerized forecasting.

In 1955, a team performed the first computerised weather forecast, marking the beginning of practical use of numerical weather prediction. The Met Office started issuing marine weather forecasts via radio transmission in 1911, and the first daily weather forecasts were published in The Times on August 1, 1861.

Numerical methods now use approximate solutions with different models employing various solution methods such as spectral and finite difference methods. Persistence forecasting relies on today’s conditions to forecast tomorrow’s weather, which can be valid in certain situations but becomes inaccurate in fluctuating patterns.

Modern Tools and Techniques

Measurements of barometric pressure and pressure tendency have been used since the late 19th century. Larger changes in pressure are associated with larger changes in weather, while rapid pressure drops indicate low-pressure systems approaching rain.

The condition of the sky is also important, especially in mountainous areas. Thickening cloud cover can indicate rain, high thin cirrostratus clouds create halos around the sun or moon indicating a warm front, and clear skies are indicative of fair weather.

Artificial Intelligence in Weather Forecasting

The analog technique involves recalling a previous weather event that is expected to be mimicked by an upcoming event. This can be difficult due to rarely finding a perfect analog for future events. Some call this type of forecasting pattern recognition.

Initial attempts to use artificial intelligence began in the 2010s, with models like Huawei’s Pangu-Weather, Google’s GraphCast, WindBorne’s WeatherMesh model, Nvidia’s FourCastNet, and the European Centre for Medium-Range Weather Forecasts’ Artificial Intelligence/Integrated Forecasting System (AIFS) appearing in 2022–2023.

Impact of Weather Forecasts

The accuracy of weather forecasts is crucial for various sectors. Thunderstorms can create strong winds and dangerous lightning strikes that can lead to deaths, power outages, and widespread hail damage. Heavy snow or rain can bring transportation and commerce to a stand-still, as well as cause flooding in low-lying areas.

A major part of modern weather forecasting is the severe weather alerts and advisories issued by national weather services when severe or hazardous weather is expected. The low temperature forecast for the current day is calculated using the lowest temperature found between 7 pm that evening through 7 am the following morning, making today’s forecasted low most likely tomorrow’s low temperature.

Specialized Weather Forecasting Services

Varying sectors require specialized weather forecasting services. Air traffic needs to prevent landing and taking off difficulties, turbulence, icing, and severe damage from thunderstorms, volcanic ash, and strong winds. Marine services need detailed marine weather forecasts transmitted via radio for safe navigation.

Agriculture requires information on suitable workdays, crop management, and preventing damage from frosts and freezes. Forestry needs to predict wind, precipitation, and humidity to prevent and control wildfires, as well as forecast conditions for harmful insects. Utility companies anticipate electricity and gas demand based on weather forecasts, particularly in response to heating or cooling degree days.

Private companies use weather forecasts to adjust business strategies, invest in commodity markets, and avoid losses. The British Royal Navy and US military have specialized branches for weather forecasting to support their operations, with a focus on accuracy and timely information for pilots, sailors, and other personnel. Military forecasters also provide pre-flight briefs and real-time resource protection services.

In conclusion, weather forecasting has come a long way from ancient observations and early scientific methods. Today’s advanced models and AI techniques continue to improve accuracy and reliability, ensuring better protection for lives and property, agriculture, utility demand estimation, and everyday planning.