Weather forecasts have come a long way in recent decades thanks to advances in technology, computing power, and weather modeling. But just how accurate are forecasts that try to predict conditions a week in advance? There are a lot of factors that come into play.
How far out can we reliably forecast the weather?
In general, weather forecasts tend to be most accurate within the first 3 days and then decrease in reliability further out. According to the National Oceanic and Atmospheric Administration (NOAA), today’s 5-day forecasts are nearly as accurate as 3-day forecasts were 30 years ago.
Beyond 5 days, accuracy drops off more rapidly but forecasts can still provide useful information out to 7-10 days. Anything beyond 10 days is highly uncertain.
Day 1 and 2 forecasts
We now have the capability to forecast the weather with a high degree of accuracy for the next 1 to 2 days. This is because weather conditions don’t tend to change radically over short 24-48 hour periods. We have a very good handle on existing conditions thanks to weather satellites, surface observations, weather balloons and other data sources.
NOAA states that forecasts for the next day (day 1) have achieved an average accuracy of around 90-95%. Day 2 forecasts aren’t far behind at 85%. These forecasts verify correctly about 9 times out of 10.
Predictions of general weather parameters like temperature, pressure, precipitation type and probability, humidity, cloud cover and wind are all usually very reliable for the next couple of days. The exact timing of precipitation is harder, but still generally accurate. Specific precipitation amounts are trickier too, especially for winter storms.
Days 3-7 forecasts
As the forecast timeframe extends to days 3 thru 7, accuracy begins to decline noticeably. NOAA’s average accuracy statistics are as follows:
- Day 3: 80%
- Day 4: 70%
- Day 5: 65%
- Day 6: 60%
- Day 7: 50%
You can see the sharp drop off. By day 7, forecasts are only about 50% accurate, essentially the same accuracy as a random chance forecast. This does not mean the forecasts are useless! Just less precise.
There are still important weather trends and potential impactful weather events like snowstorms that can be identified this far in advance. For example, the models might suggest a strong winter storm affecting the Midwest 6 days away. While the details will undoubtedly change over the next several days, preparations could begin for a significant snowfall event.
Factors impacting forecast accuracy
Why does forecast accuracy decrease so much by day 7? There are a few key reasons:
Chaotic nature of atmosphere
The equations used in computer weather models to predict the atmosphere are highly complex. Small errors can grow rapidly, a phenomenon known as the “butterfly effect.” Different runs of computer models will show divergence by 7 days out.
Model uncertainty
No weather model is perfect. There are approximations and assumptions built in, limited computing power, and difficulty representing all physical processes. Different weather models will show different solutions.
Observation errors
Observational data fed into models contains inherent errors and sparse coverage, especially over oceans.
External influences
Factors like volcanic eruptions can affect global weather in ways models cannot foresee far in advance.
With all these uncertainties, any small error in the initial conditions used for a computer forecast model can lead to very different weather solutions 7 days later. These kinds of errors grow larger with time.
Recent improvements in medium-range forecasting
Despite the inherent challenges, meteorologists have made steady progress in improving medium range (3 to 7 day) forecast accuracy over the last few decades.
A 2021 study by NOAA found these average accuracy improvements from 1994 to 2017:
| Forecast Day | 1-Day Improvement per Decade |
|---|---|
| Day 5 | 2.5% |
| Day 6 | 2.8% |
| Day 7 | 3.3% |
The improvement for day 7 is especially notable. Researchers attributed these gains to:
- Better weather models
- Increased model ensemble approaches
- Improved use of satellite data
- Better statistical post-processing
With forecast models continuing to advance, we can expect further incremental improvements in the coming years. Machine learning holds promise to one day help boost accuracy.
Role of humans in forecast process
It’s important to note that while computers are doing the heavy number crunching, human forecasters play a pivotal role in the prediction process. Meteorologists interpret the computer guidance, weigh different model solutions, analyze trends, and make adjustments based on their expertise.
Humans excel at pattern recognition from years of forecasting experience. People also use conceptual models of how the atmosphere works along with an understanding of model strengths and weaknesses. This combination of human insight and computer power yields the most accurate forecasts.
Communicating forecast uncertainty
While exact forecasts a week away are impossible, meteorologists are getting better at communicating forecast uncertainty to the public. Terms like “chance of precipitation” and probability of different temperature ranges are examples.
Weather graphics that show a range of possible solutions from different forecast models is another good way to visually represent uncertainty.
The public should understand that forecasts farther out are forecasts of possibilities, not certainties. Flexibility is required as changes occur.
Conclusion
In summary, weather forecasts continue to provide useful guidance out to a week in advance thanks to ongoing progress, but uncertainty grows rapidly. Outlooks beyond 5 days should be treated more as general trends and possibilities. Pay close attention as forecasts are refined nearer to the event. Ultimately, Mother Nature has the last say in what happens!