"In classrooms across the world, students learn that weather is what's happening at a particular moment, while climate is the long-term pattern. And yet, climate is more than long-term weather. That means that researchers who build mathematical models of Earth's climate have to account for many variables that meteorologists can safely ignore. For example, a slight change in global cloud cover makes relatively little difference to next week's weather forecast, but such a change could fundamentally alter the climate 30 years in the future."
"Due to the chaotic nature of the climate system, small differences can cause radically different futures... Visit Columbia Engineering to read the rest of the story. This website uses cookies as well as similar tools and technologies to understand visitors' experiences. By continuing to use this website, you consent to Columbia University's usage of cookies and similar technologies, in accordance with the Columbia University Website Cookie Notice."
Weather describes immediate atmospheric conditions while climate denotes long-term patterns. Climate modeling must include many variables beyond those used in weather forecasting because small shifts can compound over decades. Global cloud cover provides an example: minimal impact on next week's forecast can translate into profound climate changes over 30 years. The climate system's chaotic nature amplifies small differences, producing divergent long-term outcomes. Accurate long-term projections therefore depend on capturing subtle processes and interactions that may be irrelevant to short-term meteorological predictions. Model sensitivity to initial conditions makes robust climate prediction challenging but essential.
Read at State of the Planet
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