Weather forecast accuracy decreases with time. The greatest accuracy occurs with a Nowcast which is giving the current weather conditions and expected weather for a short time after. The least accuracy occurs in the longer term forecasts such as 6 days out or more. Another consideration is the specifics that are asked within the forecast. Shorter term forecasts tend to focus more on specifics (i.e. this area will get storms, the high will be near 80 F). Medium term forecasts such as in the 3 to 5 day time period have more generalities (i.e. high temperature in low 80ís, low temperature in upper 60s, chance of storms). Longer term forecasts that are beyond 5 days (and especially beyond 10 days out) start trending toward a comparison to climatological values (high temperature above average, threat of precipitation less than climatological normal). Thus, shorter term forecasts allow for more specifics while longer term forecasts tend to be more general and climatologically leaning. This helps compensate for the decrease in forecast accuracy with time.

Why does forecast accuracy decrease with time? One reason is due to error magnification and analysis error magnification. Small errors in the weather analysis will lead to big errors with time. This is a reason why different forecast models can have varying outputs in the long term forecast. An analogy is time spent on reading. Think of the difference between reading for 15 minutes and day and reading 30 minutes per day. After one day, the difference is reading time is only 15 minutes. But after 10 days the difference in reading time is 150 minutes. This comes out to 2.5 hours in difference in reading time after 10 days when comparing the two. Thus, a small amount of change in the decision for what to do each day at the start results in large differences in what can be accomplished in the long term. The atmosphere works generally the same way in that a small change in the short term analysis will lead to big changes in the cumulative long term. Another reason for forecast accuracy decreasing is the inability to analysis the atmosphere at all scales and all locations within the atmosphere. It becomes impractical and too expensive to analysis the atmosphere with a very fine pattern. Only so many locations can be monitored for weather data and only a small fraction of the atmosphere can be examined with direct measuring devices. Thus, not knowing exactly what is happening between observation points introduces inaccuracies into the weather data that magnify with time. A third reason is due to scale amplification. Very small size events, such as a leaf falling from a tree and moving the air molecules around it, have basically no impact on the weather in the short term. However, that small change in air motion will influence the weather in longer time frames for the same reasons as explained in the first reason in the paragraph. For these reasons, it is safe to say that long term weather predictions that give specifics will often be incorrect. Chaos wins over certainty in long term weather forecasts.