Contents (click to enlarge)
- How does the weather forecast work?
- What are these observational data?
- Who is making this weather forecast?
- How accurate are the weather forecasts?
weather stations,satellites, sea buoys, passenger planes and ships collect data from all over the world. In total, billions of observations are made every day. Processing this data with supercomputers is critical to weather forecasting in North America. The anticipation of impending tornadoes and other catastrophic weather events makes the difference between prosperity and ruin.
Whenever we decide to go outside, we usually check the weather forecast for the day. We usually do this by messaging or using mobile phones. This daily check helps us decide whether we need an umbrella or sunglasses. The weather forecast also informs people about certain weather events to be expected in the distant future so that they can prepare for them. Weather forecasting has made our lives so much easier, but have you ever wondered how these providers know what the weather will be like?
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How does the weather forecast work?
Collecting data from various sources
The answer to the timeless question of how weather forecasting works has its roots in observational data, mathematical models, and calculations. Various sources such as weather stations, satellites, sea buoys, commercial aircraft and ships collect data from around the world. Yes, even your commercial flights are a source of data! In total, billions of observations are made every day.
Weather forecasting with so many data points is especially important for weather forecasting in North America, where severe weather fluctuations are common. Especially in the USA, with its vast area and different climatic conditions, it is more prone than many other areas to hailstorms, flash floods and tornadoes. In coastal counties alone, which are highly hurricane-prone, the lives of fifty million people are at risk. Early anticipation of impending tornadoes and other catastrophic weather events makes the difference between prosperity and ruin - between life and death!
Processing this data using supercomputers
Ordinary desktop computers or laptops that we use every day are not suitable for working with the huge amounts of weather data generated by various instruments. Most weather agencies now use supercomputers with incredible computing power. For example, the National Oceanic and Atmospheric Administration (NOAA) supercomputers can perform 2.8 quadrillion calculations (yes, you read that right. 1 quadrillion is 1015) every second! These supercomputers are now crucial in making global predictions.
The supercomputers are programmed to use mathematical models based on past weather patterns and the geography of each region. The mathematical models are in the form of equations that describe important processes that govern the weather, such as Earth's rotation, wind speed and direction, precipitation, evaporation, etc. When these data points are sent from various gauges and sensors to supercomputers, they run a series of complex equations depending on how they are modeling by a meteorologist and generating a forecast.
The models used for weather forecasting are not universal; Some are good at forecasting hurricanes, while others are good at forecasting general temperature and humidity. Because of this, computers don't really have the last word. The results obtained are converted into user-friendly graphs and graphs, which can then be interpreted by weather agency meteorologists to create a more comprehensive and informed forecast.

Below is an image of what a normal forecast graph looks like and how meteorologists interpret it. The yellow dashed line would represent areas of moderate to severe turbulence, while the wavy lines represent cumulonimbus clouds, which are basically thunderstorm clouds. Thunderstorms and precipitation are more common in these areas. Green lines indicate jet streams near the core of maximum winds.
Also read:Why is the weather so hard to predict?
What are these observational data?
When creating a weather forecast, meteorologists mainly focus on observational data points. Observational data is a list of factors that influence the weather in one way or another. However, remember that everything matters. Let's take a look at some of the details of these key observational data points.
temperature and humidity
One of the things we monitor daily is temperature. An increase in temperature will most likely lead to a direct increase in evaporation. This leads to higher humidity, which increases the risk of rain, hail or snow.
pressure and wind
The next two things are pressure and wind. Depending on the pressure level, there are two types of regions: high pressure areas and low pressure areas. High-pressure areas have high-density air, and vice versa. As we know, the situation always moves from areas with a large population to areas with a low population. Similarly, winds start flowing from high pressure areas to low pressure areas. The speed of this movement depends on the pressure difference. If the difference is large, the speed is faster. The temperature difference between the two regions also has a significant impact, causing regular rain/snow and in some cases thunderstorms/tornadoes.
dew point
If you look at a glass of cold water in the sun or at the morning grass on the lawn, you will clearly see the water droplets present. These water droplets are called "dew" or condensation. When the temperature is low enough, the air is saturated with water vapor. From that moment on, we see water on the surface of glasses or windows. The temperature at which this occurs is called the "dew point". So if on a given day the temperature and dew point are close, the amount of water vapor will be greater. More water vapor leads to higher humidity, which, as mentioned above, has an additional effect on the weather.
Also read:When do the clouds get so heavy that it might rain?
Who is making this weather forecast?
Many countries rely on a single weather service provider, often controlled by the government, for weather forecasts, warnings and alerts. However, there are public, private and university weather forecasting systems in the US.
Since the United States is a large and populous country that faces large fluctuations in weather conditions over a wide area, it will likely need multiple agencies specializing in different niches to get a more accurate forecast. The United States is considered one of the world's powerhouses in weather forecasting.
Most forecasts come from the National Centers for Environmental Prediction (NCEP), part of the National Weather Service (NWS). NCEP runs various weather models and reports the results of this modeling to the NWS office, which then adjusts and optimizes the forecast depending on the region.
As already mentioned, there are also private forecasting agencies in the field of weather forecasting. For example, the commercial weather service provider Weather Underground optimizes the official forecast generated by the NWS for the neighborhood scale by overlaying information received from its own network of weather stations. Commercial players like Weather Underground help you get more accurate weather forecasts for your area. Therefore, different commercial weather service providers have their own niche. Some offer accurate local weather forecasts, others specialize in predicting climate disasters such as storms or floods.
How accurate are the weather forecasts?
You may have heard the joke that weather forecasting is the only profession where you can be wrong half the time and still not lose your job! Are weather forecasts really that inconsistent? Contrary to jokes, it is not.
Over the years, weather forecasting techniques have improved significantly. Today's weather forecasting systems are much more accurate than those of the 80's and 90's.
According toNational Oceanic and Atmospheric Administration (NOAA)The weather agency's five-day forecasts are now 90% accurate. Seven-day forecasts are about 80% accurate. These statistics become much more significant compared to historical data. For example, today's five-day hurricane forecast is more accurate than the four-day forecast from the early 2000s, and much more accurate than the three-day forecast from the early 1990s.
Although the accuracy of forecasts has greatly improved over the years, meteorologists are still a target when the weather forecast sometimes goes wrong. Also, with the advent of social media, weather data is sometimes presented out of context, giving the impression that the weather department is doing a poor job. Someone rightly said it“Meteorologists are like gatekeepers; No matter how many saves they make, they'll only be remembered for the ones they missed!"
Meteorologists admit that weather forecasting is still not an exact science. Perfectly modeling the analysis of various factors for computers can be difficult. Maybe that's the beauty of weather, that even now, with all our supercomputers, it still haunts people in the face of its tantrums!
Due to the progress of research and applicationartificial intelligenceThe weather forecast is improving significantly. According to Richard Anthes, president of the University Corporation for Atmospheric Research, in a few years the weather forecast will be basically perfect for a period of zero to two days. Well, if we can do that, we can be absolutely sure of the weather for at least a day or two, and we can better plan our trips and trips without worrying about the weather forecast being completely wrong!
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References (click to enlarge)
- Predict the weather - SEO title. ussartf.org
- Judt, F. (2020, January). Atmospheric predictability in the tropics, mid-latitudes, and polar regions studied with global storm resolution simulations. Journal of Atmospheric Sciences. American Meteorological Society.
- Judt, F. & Chen, S.S. (2016, November). Predictability and dynamics of rapid intensification of tropical cyclones obtained from high-resolution stochastic ensembles. Monthly weather overview. American Meteorological Society.
- Improvement of weather forecasts - NOAA. National Oceanic and Atmospheric Administration
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