Technology advancement contributes to faster and more assertive weather forecasting

Wake up and look at the weather forecast. This is the routine of most people. After all, no one wants to be caught by surprise by a cold front or by a sudden rain when leaving home. Weather forecasts are important allies when planning our day, either with daily newsletters or through alerts about the arrival of severe weather conditions.

What few know is that the level of accuracy and how far weather forecasts can go is far beyond what anyone could have imagined 30 years ago. The significant improvement in relation to computers, satellites and radars has been driven by technological advancement in recent years.

When it comes to radar technology, for example, updates on dual polarizations allow meteorologists to better estimate rainfall and what kind of rain is coming, as well as identify birds or tornado debris.

One of the areas that most demanded improvements is the technology used in the supercomputers that make climate forecasts. To demonstrate how far the processing power for these systems has come, a new smartphone, for example, has much more processing power than the supercomputers used in weather forecasting in the late 1980s and early 1990s. Currently, however, supercomputers are 10,000 times faster than common computers.

Satellite technology has also improved a lot in recent decades. The satellites used to make weather forecasts are currently able to report a much larger amount of data, in addition to providing images more quickly. Earlier satellite technology only allowed the sending of data and images every 30 minutes. Currently, in the event of bad weather, for example, satellites can zoom in and focus on the event of bad weather and send images every 10 seconds.

 

The three stages of meteorology: observation, analysis, and communication

According to the portal The Conversation  ,   there are three important stages of the weather. For observation, meteorologists work with atmospheric models that, according to the article, are sets of equations that describe the state of the atmosphere. The models use information about the initial state (observation) of the atmosphere, land, and ocean to predict the weather. Model data is combined with information extracted from weather stations that are installed at key points in a region or country to provide the actual state of the atmosphere. This assimilation of data produces a better prediction, as it optimizes meteorologists’ understanding of the evolving climate system.

The article also highlights that it is easier to be accurate when providing a short-term forecast – covering hours or days – than when interpreting long-term data (months or seasons). The atmospheric system is dynamic; the more time passes the less certain predictors may be of its state.

Technological advances have greatly improved the overall quality of weather forecasting. For example, more observations are possible due to automated weather stations. There was also an increase in the use of high-performance computing. This allows faster data storage, processing, and analysis of incoming data.

These sets of information are critical in diagnosing past and current time to create a forecast. In 30 years we have evolved a lot in this regard, but the rapid technological advance worldwide should make the weather forecast even faster and more assertive in the coming years.