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Location, location, location. Surface temperature patterns play a fundamental role in Earth’s energy budget.

In oceanography, as in any scientific field, the goal is not to eliminate uncertainty in data, but instead to better quantify and clearly communicate its size and nature.

To get weather and climate forecasts right, we need to think much smaller. Think of it in terms of space. Many climate models break the Earth into a grid, with each square 100 km, or 62-ish miles, a side. Smaller storms are averaged out. The small-scale landscape features that drive convection, or cloud formation, aren’t considered. But, without taking actual landscape data and smaller clouds into account, forecasts and climate models won’t be accurate. They’ll think too big and miss too much.

A new study found that global warming is making it more challenging to predict ocean conditions, manage ecosystems and prepare for marine hazards.

Kris Karnauskas is a Fellow of the Cooperative Institute for Research in Environmental Sciences (CIRES) and an Associate Professor in the Department of Atmospheric and Oceanic Sciences (ATOC) at the University of Colorado Boulder, with secondary faculty appointments in the CU School of Medicine and the Colorado School of Public Health. Prior to joining the CU Boulder faculty, Kris spent six years on the faculty of the Woods Hole Oceanographic Institution (WHOI) and the MIT-WHOI Joint Program in Oceanography (also teaching at Boston College) followed by sabbatical at the Institut Pierre Simon ...