Weather 2000 - FAQ Title Graphic

Q: What is the difference between short, medium and long range forecasting?
A: Opinions differ as to the exact divisions, but a general consensus is as follows:

Short Range 1 - 7 days
Medium Range 1 week - 4 weeks
Long Range 1 month - 1 year

Additionally, "Nowcasting" is common for severe weather analysis covering 0 - 12 hours

Climate change studies can cover decade, century and millennia time scales.

Q: Is the temporal resolution the same for all forecasts?
A: No. The resolution of a forecast must be proportional to the range of the forecast. Medium range forecasts should have a resolution of a few days to a week, and long range forecasting should have a resolution of about 1-month to a season.
Q: Are long range seasonal weather forecasts possible?
A: Yes, but these forecasts must be made properly with the use of probabilities, indicating levels of confidence.

"Long range (seasonal) predictions require use of probabilities in the forecast format, regardless of whether the forecasts are derived from dynamical models, statistical models, or hybrids of the two."

- Dr. Daniel S. Wilks, Cornell University Professor of Statistical & Agricultural Meteorology, Chair of the Probability & Statistics Committee of the AMS

Q: How far in the future are individual monthly and seasonal forecasts useful?
A: Monthly and seasonal forecasts lose their validity and value beyond 9 to 12 months into the future. Extraordinary claims to the contrary are scientifically inappropriate. Beyond one year, trended analysis of a location's climatology can sometimes prove useful, but this is more of a statistical hedge, rather than a specific forecast.
Q: Are site specific long range forecasts more beneficial than using a recent 5 or 10 year average, historical data adjusted (or "cleaned") for recent warming trends, or general seasonal outlooks for the entire country?

A: These topics are closely examined on our warming trend issues FAQ page.
Q: Are long range climate forecast maps (on the Internet and from other sources) useful for pin-pointing city specific forecasts?
A: Seasonal climate forecast maps, available for the U.S. and the world, are usually qualitative, indicating which areas are more likely to be warmer/colder, or wetter/drier than normal. The key word here is likely. These forecasts do not indicate the magnitude, or amount, of warmth or cool, only the increased chance an area will be warmer or cooler. Such seasonal forecasts, including analog and climatology forecasts, are adequate for broad-brushing trends, but they do little to forecast specific weather outcomes for specific cities and weather stations.
Q: What does it mean when seasonal forecasts indicate "Climatology", "CL", or are blank in certain areas?
A: Frequently, large portions of the nation are not forecasted for at all by seasonal forecasts, such as NCEP-CPC (see graphic on right). They label this type of non-forecast as "Climatology" or "CL", which reverts back to uncertain and equal chances of anything happening. Hence, the user is left with a proverbial "coin-flip" of possible outcomes. People often mistake these blank areas as a near normal forecast, whereas in actuality, it signifies that no forecast was made.

Financial and business communities require a much more detailed and thorough approach, and should utilize Site-Specific Forecasting.

Q: Are "probability of exceedence" and automated forecasts more useful?
A: Probability of exceedence (such as those produced from CPC predictions) and automated forecasts (where the user types in the location and weather variable) are very efficient, but simply interpolate these general seasonal forecasts for various gridpoints. They may produce attractive graphs and plots, but customized Site-Specific Forecasting will always yield greater detail, precision and accuracy.