Arctic Science Explained: Arctic Models

May 4, 2022
By Liz Weinberg

By Katherine Schexneider

Welcome to Arctic Science Explained! Each month, IARPC Collaborations community member Katherine Schexneider breaks down a topic related to Arctic science. If you have a topic you’d like to see featured, please email web@iarpccollaborations.org. This month, Katherine explains Arctic models.

Anxiety came to me when I saw the photograph: the German research ice-breaking vessel Polarstern arrived at the North Pole on August 17, 2020, as part of its year-long mission to study the Arctic Ocean and its environs. Cameras captured the scene and were widely shared. Was it a vast frozen landscape, white and barren as far as the eye could see? No. There was open water. You couldn’t miss it, and you couldn’t help but gasp. Broken up ice floes intermingled with patches of deep blue waters made the perfect metaphor for our planet’s climate: broken, damaged, maybe irreparably.

ice and melt ponds seen from the bow of a research vessel

Sea ice interspersed with melt ponds stretches in front of Polarstern. Photo via NASA

My anxiety was only partly lessened by onboard sea ice geophysicist Melinda Webster’s blog for NASA where she described about half the “open water” to be melt ponds—water on top of ice—and the other half open through to the ocean. For many years, the North Pole had thick, multiyear ice, but now the ice near the pole was thin, making Polarstern’s transit faster and easier than expected. While this was a shock to see, it wasn’t entirely unexpected: many mathematical models had suggested the melt was on its way.

What is a model? A model is system of equations that describes the processes of Earth. It’s a picture using mostly numbers.

A model begins with processes that are happening in the world around us, like ice melting, temperatures rising, wind, and rain. You probably already know how some of these are interconnected—higher temperatures mean more melting ice, for example—but there are many different processes happening at once in the Earth system. Integrating them all takes high-level math and physics and supercomputers.

Here's a simple model: Isaac Newton discovered gravity in the 17th century when an apple fell on his head (the story goes). He came up with an equation describing how fast objects fell. His model only included one Earth system force—namely, gravity—and we see this in action every time we drop something. Newton’s model helps us predict how gravity will function in other scenarios. Newton developed other equations to put numbers on what we see in the physical Earth, and garnered this epitaph from English poet Alexander Pope: “Nature, and Nature's Laws lay hid in Night, but God said, ‘Let Newton be!’ and All was Light."

Fast forward four centuries and modelers are still unveiling the laws of physics, chemistry, and biology to better understand melting sea ice and all the other inherently coupled systems of the Arctic environment. They are using satellites and supercomputers (the Department of Energy has the nation’s largest), and they are adding multiple different models together to improve their accuracy. They conduct rigorous validations where they compare their models with on-the-ground observations. It’s like a weather model predicting rain on Tuesday. Well, now it’s Wednesday, and did it rain?

Numerous models are used to predict how the Arctic will act under climate change. The Community Ice Code (CICE) models sea ice (hence the name), using a software package to represent how the ice melts and freezes over through the seasons, and how it moves across the ocean. Now on its sixth version, it provides accurate predictions on ice dynamics to researchers, and also to shipping, tourism and fishing industries which rely on this data for their daily work. Another example is the Integrated Ecosystem Model, which pulls together models on permafrost, the terrestrial ecosystem, and fire disturbances to understand and predict how the systems impact one another. Other models help predict wave patterns, storm tracks and intensity, the impact of Arctic change on the rest of the planet, and more.

Models and observations complement each other, and both have limitations. We do most of our observing in the Arctic in the summer months due to weather and daylight restrictions, so this creates a bias. And while models can predict the future with increasing accuracy, there is still much we don’t know about how different models perform under various conditions.

One doesn’t need to fully grasp the advanced mathematics to appreciate the work of the modelers studying the Arctic. It is warming faster than the Earth as a whole, and dedicated people are building the equations that can tell us how fast sea ice and glaciers will melt, how high temperatures will rise, when species may die off, and many other climate phenomena. But can they make sense of the Arctic climate for us? I think so. Deep understanding of what forces are at work in Earth’s systems at present, and how they are most likely to change in the near term of months and years, is the foundation for adaptation and mitigation efforts. Model builders lay this foundation, setting the stage for a better future in a fragile Arctic. There’s still a lot to be anxious about, but we can take corrective action. While I am reducing my carbon footprint at home, super smart people and their supercomputers are tackling the bigger picture. And that makes sense to me.

Katherine Schexneider is a retired US Navy physician who now does volunteer work in Arctic research and climate change.

Note: Views expressed in this article are the author’s and do not necessarily reflect the views of the IARPC community.

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