Real-time data versus forecasts: how to read the data without being misled
Real-time data describe a recent measurement; a forecast describes an estimate of the future. Space-weather products often place both in one interface, but they must remain conceptually separate.
What it really means
Even the best data have limits: calibration, telemetry, time resolution, viewing geometry and propagation introduce uncertainty. Reading the original source helps explain why two apparently similar plots may not match perfectly. A very precise-looking number should not hide uncertainty. Resolution, filtering, algorithms and delays can make two valid products differ without either being wrong.
Why it matters
A scientific instrument does not automatically produce a forecast: it produces a measurement, image or model that must be interpreted. Real-time data versus forecasts becomes genuinely useful only when we know what it measures, where the data are acquired and how much delay is involved. Before using it to decide whether to go outside, determine whether you are looking at an observation, a derived product or a forecast. It is a simple distinction, but it radically changes what the plot means.
How to interpret it without oversimplifying
For Aurora Hunter, separating observation from modelling is essential. A sensor can describe what is happening now; a model combines measurements and assumptions to estimate what may happen next. Confusing the two creates false certainty.