7-Day Forecast: How It Works
A seven-day forecast is not seven equally reliable days. Accuracy falls off sharply with time, and knowing roughly where it falls off is the difference between using a forecast well and being repeatedly disappointed by it.
How accuracy decays
| Range | Typical accuracy | Use it for |
|---|---|---|
| Today | ~95% | Firm decisions |
| Tomorrow | ~90% | Firm decisions |
| 3 days | ~80% | Planning with a fallback |
| 5 days | ~70% | General expectations |
| 7 days | ~50–60% | Broad trend only |
| 10+ days | Near climatology | Little more than seasonal averages |
Beyond about ten days, forecasts converge on what is typical for the date and location. This is not a limitation of computing power but of the atmosphere: small differences in initial conditions grow exponentially, which places a hard theoretical ceiling on deterministic forecasting at around two weeks.
What 'chance of rain' means
A 40% chance of rain does not mean light rain, or rain for 40% of the day. Most services define it as the probability that measurable precipitation — usually at least 0.2 mm — falls at any given point in the forecast area during the period.
Some agencies compute it as confidence multiplied by area coverage: 80% confident that rain will cover half the region gives 40%. Either way, it is a probability, and a 30% chance means it will rain on roughly three of every ten such days. Days when it does not rain are not failures of the forecast.
Temperature is the reliable part
Forecast temperature is considerably more accurate than forecast precipitation, and holds up further out. Rain depends on small-scale processes — convection, local terrain, individual storm cells — that models resolve poorly. A five-day temperature forecast is usually worth trusting; a five-day forecast of a specific afternoon shower is not.
Where forecasts struggle most
- Summer thunderstorms — models predict the conditions, not which town gets hit.
- Snow amounts — a degree or two decides rain, sleet or snow, and changes totals dramatically.
- Mountains and coasts — terrain creates local effects finer than the model grid.
- Fog — depends on very small temperature and moisture margins.
Reading a forecast well
- Trust days one and two; treat day seven as a trend.
- Watch how the forecast changes across successive updates — a stable forecast is more trustworthy than one that swings.
- Read the temperature range rather than only the high.
- Note the wind, which affects comfort as much as temperature.
- For anything important, check again the morning of.
Why services disagree
Different providers run different models, or post-process the same model output differently. Disagreement between them is itself information: when several forecasts agree, confidence is high; when they diverge, the situation is genuinely uncertain and worth a fallback plan.