Testing Arctic climate models: how much detail can we capture?

Many of us have heard that as a consequence of climate change, Arctic sea ice is rapidly decreasing and that the Arctic is warming twice as fast as the rest of the planet. It’s a complicated system that we don’t understand very well: few people live in the Arctic, and the data from limited study sites may not be representative of the region as a whole. How will Arctic climates change at different timescales in the coming years? What could this mean for coastal Arctic communities that rely on sea ice for preventing erosion or fishing in deep waters? How will navigation and shipping routes change? And in addition, how does a changing Arctic affect climates at lower latitudes?

Visualization of winter sea ice in the Arctic by Cindy Starr, courtesy the NASA Scientific Visualization Studio.

Daniel Watkins is a fourth-year PhD student of Atmospheric Science in OSU’s College of Earth, Ocean, and Atmospheric Science (CEOAS). Working with Dr. Jennifer Hutchings, he is analyzing climate model experiments in order to find answers to these questions. An important step in this is to evaluate the quality of climate simulations, which he does by matching up model output with real-life observations of temperature, sea ice, and cloud cover. Climate scientists have many models that predict how these factors will change in the Arctic over the next several decades. No model can take every detail into account, so how accurate can its predictions be? For example, the frigid Arctic temperatures can cause water molecules in low-lying clouds to trap heat in a very different way than they do here in the Pacific Northwest. Is it necessary to take a detail like this into account?

In cold regions like the Arctic where surface ocean temperatures are much warmer than the overlying atmosphere, the ocean transfers a lot of heat into the air. Sea ice insulates the ocean and prevents heat transfer to the atmosphere, so when there is less ice, a cycle of increasing warming can perpetuate. Because water has a higher heat capacity than air, the ocean doesn’t cool off as much as the atmosphere warms. This is particularly bad news for the Arctic, where layers of cold, dense air often sit beneath warmer air in a phenomenon called a temperature inversion. Effectively, this prevents heat from moving on to higher layers of the atmosphere, so it stays low where it could melt more sea ice. This contributes to a phenomenon called Arctic Amplification, where for every degree of warming seen in the global average, the Arctic surface temperature warms by about four degrees. While it may be tempting to build a model containing every cloud in the atmosphere or chunk of ice in the Arctic Ocean, these could make it too computationally difficult to solve. Daniel has to simplify, because his goal is not to provide a weather forecast, but to evaluate how well models match observed measurements of Arctic temperatures.

Daniel by the Skogafoss in Iceland in June 2018. If you’re lucky (and he was), you can see sea ice, turbulent boundary layer cloud layers, and the Greenland ice sheet when you fly between Portland and Iceland.

To accomplish this, Daniel uses model output data, re-analyzed data that fits models to observations, and temperature measurements from weather balloons. These sources contain terabytes of data, so he has written code and contributed to open-source software that subsets and analyzes these datasets in a meaningful way. Daniel then uses the re-analyzed and weather balloon data to test whether the model reproduces various features of the Arctic climate, such as widespread temperature inversions. Working with this vast amount of information requires some mathematical prowess. While studying as an undergraduate at BYU Idaho, Daniel decided to major in math when he heard a professor describe mathematics as “a toolbox to solve science problems with”. An internship at Los Alamos National Laboratory later suggested geophysical modeling as a worthy task to tackle.

When he’s not modeling the future of the Arctic, Daniel spends time with his children, Milo and Owen, and plays in a rock band he formed with his wife, Suzanne, called Mons La Hire. Daniel is also a DJ on KBVR and is excited to become the newest host of Inspiration Dissemination. To hear more, tune in on Sunday, December 2nd at 7 PM on KBVR 88.7 FM, live stream the show, or catch our podcast!

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