Global Temperature Anomaly Network

Climate analytics rarely looks at raw temperature — it looks at how far each place deviates from its own historical normal. This simulator scatters a network of stations across a 3D globe, gives each one a latitude- and season-dependent climatological baseline, and then drives a live reading that drifts with a long-term warming trend, a wandering ENSO-like warm/cool patch, and small day-to-day noise. Every station's anomaly is converted to a z-score against its expected variability and colour-coded on a cold-to-hot diverging scale, and stations crossing your chosen threshold pulse and are counted live — the same detect-and-flag workflow real climate-monitoring pipelines use on satellite and ground-station data.