Forecast Range Types:
Before examining why longer-term forecasts are less accurate than current forecasts, timeanddate.com looks at basic definitions on the types of weather forecasts made in relation to time:
A short-range forecast is a weather forecast made for a time period up to 48 hours.
Extended forecasts are for a period extending beyond three or more days (eg. a three to five-day period) from the day of issuance.
Medium range forecasts are for a period extending from about three days to seven days in advance.
Long-range forecasts are for a period greater than seven days in advance but there are no absolute limits to the period.
Short-range forecast predictions, where the forecast is made for a time period for today and/or tomorrow (up to 48 hours), are generally more accurate than the other types of forecasts.
Why Are Longer-Term Forecasts Less Accurate?
Weather forecasts still have their limitations despite the use of modern technology and improved techniques to predict the weather. For example, weather forecasts for today or tomorrow are likely to be more dependable than predictions about the weather about two weeks from now. Some sources state that weather forecast accuracy falls significantly beyond about 10 days.
Weather forecasting is complex and not always accurate, especially for days further in the future, because the weather can be chaotic and unpredictable. For example, rain or snow cannot always be predicted with a simple yes or no. Moreover, the Earth’s atmosphere is a complicated system that is affected by many factors and can react in different ways.
If weather patterns are relatively stable, the persistence method of forecasting provides a relatively useful technique to predict the weather for the next day. If it is hot and sunny on one day, it is likely to be hot and sunny the next. However, the weather in many parts of the world is more unpredictable and changeable than that, particularly in the mid-latitudes where depressions influence much of the weather.
Depressions, sometimes called mid-latitude cyclones, are areas of low pressure located between 30 degrees and 60 degrees latitude. Depressions develop when warm air from the sub-tropics meets cold air from the Earth’s polar regions. Depressions usually have well defined warm and cold fronts, as the warm air is forced to rise above the cold air.
Improving Predictions:
Weather is inherently unpredictable, because so many little variables can affect it to a great degree, especially when you try to forecast something accurately more than a day out. It's pretty easy to look at a satellite photo, notice a big system of warm moist air coming in off the ocean just a hundred miles off the coast and say with a certain degree of confidence that it'll rain tomorrow.
Over the weekend? Now you're just guessing a cold gust from the north might blow the weather system down south of you before it rains on you, and the rain you predicted just doesn't happen. So the science of meteorology is part intuition, when you come right down to it you get a feeling based on what you know of historical trends for the area you're trying to forecast, given what you know of the conditions and the season of the year.
Here in Seattle, autumn usually means gray, overcast skies, with rain at least three days out of any given week, so if you say that it will be cloudy, lows in the mid 50's, highs in the upper 60's, 30% chance of precipitation, you've pretty much covered all your bases if it rains, you can say there was always that chance, and if it doesn't, you can say, "Well, it was only a 30% chance, after all!"
Weather observation techniques have improved and there have been technological advancements in predicting the weather in recent times. On average, a five-day weather forecast of today is as reliable as a two-day weather forecast 20 years ago. Despite this major scientific and technical progress, many challenges remain regarding long-term weather predictability.
The accuracy of individual weather forecasts varies significantly. The challenges include finding out more about individual forecasts’ changing uncertainties as well as improving forecasting skills in areas where progress has been difficult (such as heavy rainfall and the genesis, intensity and structure of tropical cyclones).
While most scientists are revered for making sense of our complex universe (Einstein is practically a hero), meteorologists often face ridicule. How can we put a person on the moon or foretell planetary alignments years in advance, yet still fail to put together accurate weather forecasts?
First, to give credit where credit is due: Weather forecasters have improved their game significantly over the last 20 years. The three-day forecasts they deliver today are better than the one-day forecasts they delivered 20 years ago. They're also much better equipped to provide advanced warnings of severe weather, doubling the lead times for tornado warnings and giving people an extra 40 minutes to escape flash floods.
Modern meteorologists wouldn't be nearly so accurate without numerical forecasting, which uses mathematical equations to predict the weather. Such forecasting requires powerful computers and lots of observational data collected from land, sea and air.
A single weather station would never be able to collect so much information. Instead, thousands of stations across the globe are linked and their data pooled. Some of these stations ground-based wind gauges (what meteorologists call anemometers), rain collectors and temperature sensors resemble those used by amateur weather watchers. Others lie far out at sea, strapped to buoys.
And still others travel on commercial airliners or shipping vessels, collecting weather data as passengers and goods are moved from point A to point B. Finally, weather satellites and balloons provide information from the upper regions of the atmosphere. Satellites photograph Earth's weather from their orbit in space, while balloons monitor upper-air data over a particular location.
Collectively, all of these sensors and gauges produce more than 1 million weather-related observations every day. A normal computer the kind you buy at your local electronics store would choke on all of this data. Luckily, meteorologists can rely on supercomputers, crazy-fast machines that perform millions of calculations per second. In the United States, these computers are housed at the National Centers for Environmental Prediction (NCEP), located in Camp Springs, Md. There, weather observations stream into a supercomputer's brain, which uses complex mathematical models to predict how, based on the incoming data, weather conditions might change over time. The computer's output form the basis of almost every forecast broadcast on radio and television channels across world.
Partly Cloudy with a Chance of Chaos:
You might think that the National Centers for Environmental Prediction's supercomputers could never make mistakes, but even their abilities aren't up to the enormous challenge of weather forecasting. That's because they must take into account several large-scale phenomena, each of which is governed by multiple variables and factors. For example, they must consider how the sun will heat the Earth's surface, how air pressure differences will form winds and how water-changing phases (from ice to water or water to vapor) will affect the flow of energy.
They even have to try to calculate the effects of the planet's rotation in space, which moves the Earth's surface beneath the atmosphere. Small changes in any one variable in any one of these complex calculations can profoundly affect future weather.
In the 1960s, an MIT meteorologist by the name of Edward Lorenz came up with an apt description of this problem. He called it the butterfly effect, referring to how a butterfly flapping its wings in Asia could drastically alter the weather in City. Today, Lorenz is known as the father of chaos theory, a set of scientific principles describing highly complex systems, such as weather systems, where small changes in initial conditions radically change the final results. Because of chaos, there is a limit to how accurate weather forecasts can be. Lorenz set this limit at two weeks.
Modern meteorologists use state-of-the-art technology and techniques to tame chaos, such as the ensemble forecast, which consists of several forecasts, each one based on slightly different starting points. If each prediction in the ensemble looks the same, then the weather is likely to "behave." If any prediction looks radically different, then the weather is more likely to "misbehave."
Meteorologists also rely on Doppler radar to monitor weather conditions more effectively and improve forecasts. Doppler radar requires a transmitter to emit radio waves into the sky. The waves strike atmospheric objects and bounce back. Clouds moving away from the transmitter return different kinds of waves than clouds moving toward the transmitter. A computer in the radar converts data about the reflected radio waves into pictures showing cloud coverage and bands of precipitation, as well as wind speeds and direction.
Because of this technology, meteorologists can now predict the weather better than ever, especially when they limit how far they look into the future. For example, up to 12 hours out, meteorologists offer fairly reliable forecasts of general conditions and trends. Unfortunately, thanks to chaos, they will never be able to predict the weather with absolute certainty, which is how surprise storms tornadoes and torrential, flooding rains continue to devastate communities with little warning. For this reason, it might be best to carry an umbrella, even on days forecasted to be bright and sunny.
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