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A series of test cases designed to confirm the accuracy of ocean models could help improve our understanding of large-scale climate processes.

Tuning parameterizations of turbulent mixing and of the fall velocity of precipitation and cloud ice alleviates long-standing biases in climate simulations.

To assess a community's risk of extreme weather, policymakers rely first on global climate models that can be run decades, and even centuries, forward in time, but only at a coarse resolution.

MIT researchers developed a method to improve predictions from large-scale climate models. When paired with smaller-scale models to predict specific weather events such as tropical cyclones or floods, the approach produced more accurate predictions for how often specific locations will experience those events over the next few decades.

A recent modeling study shows that bark beetle outbreaks in forests won’t necessarily cause bigger and more damaging wildfires — at least not for awhile.The research could someday help fire managers better decide on how to dedicate resources in fight