Climate change is not captured by any one signal — it becomes visible through patterns that appear when satellite measurements are examined together across regions and years. While NASA collects immense volumes of satellite data on rainfall, soil moisture, vegetation, wildfire, and ocean temperature, these datasets are produced by different missions and are often analyzed separately unless they are explicitly fused. Without integrating these signals into a unified view, it becomes much harder to see how large-scale climate cycles drive local disasters.

El Niño and La Niña are global climate oscillations driven by above- and below-average sea surface temperatures in the equatorial Pacific. These cycles shift the Pacific Jet Stream, alter ocean upwelling, and redistribute heat and moisture across the planet — producing opposite climate effects in different parts of the world.

‍Texas and Australia sit on opposite ends of these oscillations. During La Niña, colder Pacific waters shift the jet stream northward, bringing warmer, drier conditions to the southern United States while intensifying rainfall and flooding in parts of Australia. During El Niño these patterns reverse. Because of this, climate disasters such as drought, wildfire, flooding, and vegetation loss are expected to show inverse behavior between these two regions across ENSO cycles.

By confirming that Texas and Australia behave as climatic opposites across El Niño and La Niña cycles, our work enables more reliable forecasting of where climate disasters are likely to intensify next. When an ENSO phase begins to emerge, historical patterns can now be used to anticipate whether a region is more vulnerable to drought, wildfire, flooding, or vegetation loss. These insights support early warning systems, emergency preparedness, and long-term climate adaptation planning — helping governments and communities allocate resources before disasters reach their peak.