In meteorology, spaghetti plots show outputs from what kind of forecast members?

In meteorology, spaghetti plots show outputs from ensemble members.

An ensemble forecast runs a weather model multiple times with slightly different starting conditions, model physics, or other assumptions. Each run is called an ensemble member. A spaghetti plot places comparable output from those members on one chart, often as contour lines or projected storm tracks.

The spread of the lines gives forecasters a quick sense of uncertainty. When members cluster tightly, the forecast signal is relatively consistent. When they diverge, the atmosphere’s chaotic behavior or model uncertainty makes the outcome less certain. For example, hurricane-track plots may show many possible paths, while upper-air charts may display one pressure contour from each run.

These graphics are not the same as a single official forecast, and they do not directly provide a complete probability distribution. They are a visual diagnostic: agreement suggests confidence, while separation highlights possibilities that deserve attention. The “spaghetti” name refers to the tangled appearance of many overlaid forecast traces, not to any particular weather variable.